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[Display omitted] • Optimization study of Photo-Fenton and PDS/UV processes for BOD and COD removal. • Photo-Fenton process was able to enhance biodegradability. • PDS/UV process on the best condition only could maintain the biodegradability. • The operational cost of Photo-Fenton processes is much cheaper than PDS/UV process. The aim of this study is to provide an Advanced Oxidation Process (AOP) based solution to enhance biological treatment efficiency by improving biodegradability of wastewater. Photo-Fenton and Peroxydisulfate (PDS)/UV processes were selected in this study as a representative of hydroxyl and sulfate radical based AOPs. A central composition design (CCD) employed to optimize operational cost and BOD/COD ratio to determine optimal conditions for enhancing wastewater treatment efficiency. The study achieved a maximum COD removal of 71.5 % and increased wastewater biodegradability. Optimal conditions for Photo-Fenton process were DOD (H 2 O 2) 0.28, [Fe2+] 106.26 mg/L, and pH 2.32, costing 2.27 USD per 1 kg COD removed. For PDS/UV process, 75.5 % COD removal was achieved at a cost of 10.6 USD/1 kg removed COD. The PDS/UV process had higher COD removal than Photo-Fenton but did not improve wastewater biodegradability. Optimal conditions were DOD (PDS) 0.19, pH 6.68, costing 10.6 USD/1 kg COD removed. [ABSTRACT FROM AUTHOR]

• A Goal Programming model to optimize a waste paper recycling network was elaborated. • The model considers objectives related to sustainability, multiple products and periods. • Vehicle routing, different-capacity vehicles and multiple trips are highlights. • The possibility of storing material at the collection points is considered. • The formulation provides relevant solutions to assist decision-makers. Organization and planning of reverse logistics networks make sustainable processes more efficient. Thus, an important sector for connecting the collection and waste paper recycling echelons is the intermediate center. In this study, a Mixed Integer Linear Programming model, which is multi-objective, multi-product, multi-level and multi-period, was developed to optimize the waste paper logistics processes of intermediate centers. The formulation includes the following echelons: collection, considering vehicle routing with different capacities; inventory of non-baling materials; baling sorted waste and inventory of bales; selling bales; disposal of non-recyclable waste. The aims of the model include: maximizing the collected waste; minimizing distances; maximizing both the production and sale of bales, and minimizing costs. According to research carried out in the literature, the developed model is a new proposal and to implement it, the Weighted Goal Programming and Revised Multi-Choice Goal Programming approaches were used to deal with multiple objectives and incorporate uncertainty into the quantity of waste available for collection. To analyze the proposed model, computational tests were executed with instances based on real data from a Brazilian company in the sector. For all performed tests, General Algebraic Modeling System 23.6.5 modeling language and CPLEX 12.2.0.2 solver were used for modeling and optimization. The results show that this study presents formulation and technological approaches that represent real situations and provide competitive solutions to the problem. [ABSTRACT FROM AUTHOR]

• Italian consensus about optimization in Nuclear Medicine Therapy. • Optimization must deal with feasibility, limited resources and cost/benefit. • Non-standardized therapies are defined, according to the variability of outcome. • Supremacy of the radiation therapy legislation over the pharmacological laws. • Appeal to EMA to obtain the official acknowledgment of this principle. This recommendation by the Italian Associations of Nuclear Medicine (AIMN) and Medical Physics (AIFM) focuses on the dosimetric optimization of Nuclear Medicine Therapy (NMT) as clearly requested by the article 56 of the EURATOM Directive 2013/59 and its consequent implementation in article 158 in the Italian Law n. 101/2020. However, this statement must deal with scientific and methodological limits that still exist and, above all, with the currently available limited resources. This paper addresses these specific issues. It distinguishes among many possible kinds of NMT. For each type, dosimetric optimization is recommended or considered optional, according to the general criteria adopted in any human choice, i.e. a check of technical feasibility first, followed by a cost/benefit argument. The classification of therapies as standardized or non-standardized is presented. This is based on the complexity of the type of pathology, on the variability of the treatment outcome, and on the risks involved. According to the present document, which was officially delivered to Italian Health Ministry as necessary interpretation of the law, a therapeutic team can, in science and consciousness, overcome the indications of posology, to optimize and tailoring a treatment with dosimetry, on the basis of published national or international data or guidelines, without need of an Ethics Committee approval. Data collected in this way will provide additional evidence about optimal dosimetric reference values. As conclusion, a formal appeal is made to the European and National regulatory agencies for pharmaceuticals to obtain the official acknowledgment of this principle. [ABSTRACT FROM AUTHOR]

TiO 2 /PS composite is evaluated in photodegradation of lignin under UVA-LED irradiation. • TiO 2 /PS composite was synthesized by solvent-casting method. • The effects of operational parameters were evaluated and optimized by Box-Behnken design. • The toxicity effects after photodegradation process were not observed. • The reusability study confirmed the stability of TiO 2 /PS composite. In the present study, the photodegradation of lignin was studied using TiO 2 /Polystyrene composite under UV-LED irradiation in a batch-recirculated photoreactor as a supplementary treatment for pulp and paper industries. TiO 2 /PS composite was synthesized by the solvent-casting method and was characterized by scanning electron microscopy (SEM) and EDX analysis. The 3-level, 3-factor Box-Behnken design was applied to study the effects of main operating parameters and optimization of process circumstances. Besides, COD reduction efficiency, toxicity assays, and reusability were also investigated. The predicted model had R2 and R2 adj correlation coefficients of 0.97 and 0.99 respectively, which showed experimental results were very close to the predicted values. Furthermore, under the optimal conditions (reaction time = 72.5, volumetric flow rate = 230 mL/min and lignin = 51.8 mg/L) the lignin degradation efficiency was 93.98%. The maximum COD removal (89%) obtained by 250 mL/min volumetric flow rate and lignin concentration of 50 mg/L after 120 min reaction time. Bioassay using D. Magna exhibited that at the beginning of the process, the toxicity of solution increased but continuously decreasing after then to very low values achieved within 120 min of photodegradation. In addition, the reusability tests demonstrated that the TiO 2 /PS composite after 5 cycles has a good stability and photocatalytic activity. [ABSTRACT FROM AUTHOR]

Abstract The global demand for bio-plastic particularly polyhydroxyalkanoate (PHA) have been increased in the last few decades as a substitute of petrochemical-based plastic. Utilization of waste paper, the primary constituent of municipal solid waste (MSW), as a carbon source for polyhydroxybutyrate (PHB) production is not only an alternative, environmental friendly route of waste management but also helps to valorize the waste. In this study, hydrogen peroxide pretreated waste paper saccharification has been optimized using central composite design (CCD). The maximum hydrolysis (88.18%) occurred at paper loading 5.0 g/L, agitation 242 rpm, working volume 20%, cellulase 49.82 U/g, β-glucosidase 20.9 U/g and hemicellulase 29.5 U/g. PHB synthesis and biomass accumulation by xylose-utilizing Burkholderia sacchari using waste paper hydrolysate were studied using different nitrogen sources and carbon to nitrogen (C/N) ratios. Maximum PHB and dry cell weight (DCW) occurred with ammonium sulfate and a C/N ratio of 20. The highest biomass (3.63 g/L), the maximum PHB accumulation (44.2%) and the maximum reducing sugar utilization (92.1%) were observed after 48 h of cultivation using diluted hydrolysate. The physicochemical properties of the extracted PHB were compatible with the standard PHB. Hence, the waste paper could be exploited as a renewable feedstock for the sustainable production of PHB. Graphical abstract Image 1 Highlights • The maximum enzymatic hydrolysis 88.18% was achieved by response surface method. • PHB produced from waste paper hydrolysate using xylose utilizing B. sacchari. • Maximum PHB and dry cell weight occurred with (NH 4) 2 SO 4 and C/N ratio of 20. • High thermostability of PHB with a maximum degradation rate around ∼ 300 °C. • PHB production using waste paper is cost effective and ecofriendy approach. [ABSTRACT FROM AUTHOR]

The aim of this paper is the development of a mathematical model to compute the optimal inventory mix to face stochastic demand at minimum cost in a two-level supply chain. The paper addresses a multi-product dynamic lot-sizing problem under stochastic demand subject to capacity and service level constraints. This model is executed to compare a Make To Order (MTO) strategy to a Vendor Managed Inventory (VMI) partnership between the supplier and their customers. Both strategies provide the demand order to be produced. A schedule of production orders is determined over the planning horizon in order to minimize the inventory holding costs of the supply chain, taking into consideration that the supplier is also responsible of initiating the replenishment orders and deliveries of their customers according to the VMI partnership. The simulation model is illustrated empirically using a real case study: a paper manufacturing company that pursues to improve customer service level and supply chain inventory costs through a proper production planning of their paper machines and a suitable VMI order replenishment schedule. [ABSTRACT FROM AUTHOR]

Paper mills are among the most polluting industries, responsible for many organic and inorganic compounds emissions. The fibres electro-kinetic features strongly affect the ability to retain fillers since the fillers–fibres interactions are charge induced. The control and the prediction of these parameters would represent a precious aid for process management, allowing the fillers retention enhancement, a lower environmental impact and the paper sheet properties streamlining. The work presented deals with the implementation and training of four artificial neural networks (ANNs) for the prediction of the main electrochemical and physical features of cellulose pulp and paper. First, two ANNs predict the electrochemical parameters. Following, they were applied to predict the paper sheet properties and fillers retention. The neural models implemented showed outstanding prediction performance, with R2 in the order of 0.999 and a low mean error. The results demonstrate how Artificial Neural Networks may be a valuable instrument for paper mill pollutant reduction. However, they suggest a more inclusive investigation for a better fibres behaviour representation. • Main process parameters of an industrial papermaking process were identified. • Experimental datasets were achieved during industrial production. • Artificial Neural Networks were trained for process parameters prediction. • Accurate predictions of papermaking process were obtained. [ABSTRACT FROM AUTHOR]

This paper investigates the possibility of combining different forest industries (a pulp and paper mill, its supply chain, and a wood-pellet plant) into an integrated industrial site in which they share a common heat and power utility. Advanced process integration and optimization techniques are used to study the site from both material and energy viewpoints. An existing pulp and paper mill is used as the site core plant and its pulp and paper production rates are kept fixed as they are in reality, while the other material flow links among the plants are based on the current industrial situation in Sweden. Different scenarios are evaluated in order to reflect the two main objectives that can be pursued (increased electricity production or biomass resource saving) and the two technologies that can be considered for the shared CHP system (boilers and product gas fired gas turbines). The corresponding non-integrated (standalone) configurations are compared to these scenarios to quantify the potential benefits of the integration. Investment opportunity is also calculated for the considered scenarios as an indicator of the economic convenience. [ABSTRACT FROM AUTHOR]

[Display omitted] • Waste office paper was utilized as a substrate for microbial lipid production. • A detailed optimization study has been conducted for biomass and lipid yield. • Optimization results in10.55 g/L biomass, 6.13 g/L lipid with 58% lipid content. • Biodiesel properties of the produced lipids met with the international standards. • A solution to mitigate the hazardous effects caused by waste and fossil fuel. Environmental issues caused by fossil fuel and its rapid depletion demand the need to produce biofuel from renewable energy resources. The disposal of waste paper in landfills causes air pollution and contaminates groundwater. Hence, exploiting paper waste as a renewable resource for microbial lipid production can solve these environmental issues in a greener way. Further, these microbial lipids are a reliable source for biodiesel production. In this study, waste office paper was utilized as a substrate to produce microbial lipids through fermentation by the oleaginous yeast, Rhodosporidium toruloides, using a biorefinery approach. The production conditions were optimized using the Box-Behnken design; a fermentation time of 116.16 h, a C/N ratio of 60, and an inoculum concentration of 9.67% yielded a biomass of 10.55 g/L and a lipid yield of 6.13 g/L with a total lipid content of 58%. The major lipids produced were oleic acid (42%), palmitic acid (36%), stearic acid (9.8%), and myristic acid (8%), which clearly indicates the suitability of the lipids produced by R. toruloides for biodiesel production. The predicted biodiesel properties of the transesterified product met the international standard specifications. Hence, utilizing waste office paper for biodiesel production will be an effective way of mitigating the environmental pollution caused by waste paper and the harvesting of fossil fuels. [ABSTRACT FROM AUTHOR]

Abstract: The aim of the study is to model and to simulate the thermal and electrical efficiencies of the cogeneration plant of a paper mill. The final purpose is the benefits optimization by adjusting production to the amount of energy to be sold. It is necessary to know it because the sale price goes down when the actual production of electrical energy does not match the scheduled power. [Copyright &y& Elsevier]

To address the growing need for economically viable sludge processing technologies and associated resource recovery, a novel convective high-velocity pilot cyclone was set-up at the Swedish University of Agricultural Sciences in Umeå, Sweden. In essence this process entails feeding (⩽900 kg h −1 ) a material to a heated high-velocity air flow (approx. 13 × 10 3 m 3 h −1 ) allowing moisture removal at low temperatures. This equipment is expected to improve drying of challenging industrial sludge materials when used as a pretreatment method prior to further processing. Modeling results based on an experimental campaign on recycled paper mill sludge indicated that efficient drying with a specific energy consumption of ⩽1–1.2 kWh kg −1 H 2 O can be achieved with inlet air temperature levels ⩾40 °C coupled with respective feeding capacity of ⩽750 kg h −1. [ABSTRACT FROM AUTHOR]

Abstract: Laboratory scale research on the effects of operating parameters, including mixed liquor suspended solid (MLSS) concentration, volumetric exchange rate (VER), aeration time, temperature and daily operation cycle on biological treatment of the pulp and paper mill effluent was studied using four 4l sequencing batch reactors (SBR). The results revealed that chemical oxygen demand (COD) removal efficiency was up to 93.1±0.3% and the volumetric loading reached 1.9kgBODm−3 day−1 under optimal operating conditions. The treatment performance of organic removal by the SBR system remained stable during the operation. The effluent quality was satisfied with the discharge standard set by the local authority and the filamentous bulking problem was solved. At the same time, the sludge settleability, in terms of sludge volume index (SVI), was improved to the healthy level (SVI=52.7±1.3mlg−1). [Copyright &y& Elsevier]

Abstract: Filamentous foaming and bulking in activated sludge process are common problems in pulp and paper mill wastewater treatment processes. In this study, the predominant foaming and bulking causing filamentous microorganism in the pulp and paper mill effluent treatment system was identified. Its growth kinetics was studied and used as a theoretical basis to develop an optimal operational strategy for foaming and bulking preventive control. Filamentous actinomycetes, Nocardia amarae was found to be the predominant filamentous microorganisms. The kinetics study revealed that the Food to Microorganism (F/M) ratio was a critical factor affecting the excessive growth of N. amarae. Accordingly, a novel Feast-Fast Operation (FFO) strategy was developed, in which the sludge microbes underwent a repetitive switch between high and low F/M ratio during the course of wastewater treatment. Feast-to-Fast Loading Ratio (FFLR) was proposed and used as the parameter for optimization of FFO performance. At FFLR of 4 and 3.5, the sludge volume index (SVI) rapidly reduced to a healthy level of 70mlg−1 and the systems were free from stable foam, while the biochemical oxygen demand (BOD) removal efficiency remained above 96.2%. The FFO strategy effectively suppressed filamentous overgrowth and improved the settleability of activated sludge without adversely affecting the BOD removal efficiency. [Copyright &y& Elsevier]

Two types of waste paper materials, newspaper and office paper, were evaluated for their potential to be used as renewable feedstock for the production of fermentable sugars via the enzymatic hydrolysis of their cellulose fractions. The effects of four factors (hydrolysis time, enzyme loading, surfactant addition and phosphoric acid pretreatment) on the extent of sugar yield were assessed and quantified by using a methodical approach based on response surface methodology. The statistical experimental design used in this study requires fewer experimental runs compared to some commonly used experimental designs. In the newspaper hydrolysis case, response surface plots revealed that the degree of sugar release increased with an increase in hydrolysis time but it was hardly affected by the enzyme loading and acid pretreatment factors. The surfactant addition factor exhibited a positive effect when the enzyme loading level was relatively low. With office paper as the substrate, three of the four factors (hydrolysis time, enzyme loading and acid pretreatment) exhibited positive effects on the extent of sugar release. At local optimum conditions, the maximum sugar yield from office paper was found to be 0.82 g of reducing sugars per gram of paper, which was about 4.8 times higher than the maximum sugar release from the newspaper substrate. [ABSTRACT FROM AUTHOR]

Abstract: In this study geno-toxicity analysis along with effluent treatment was taken up to evaluate the efficiency of biological treatment process for safe disposal of treated effluent. Four fungi were isolated from sediments of pulp and paper mill in which PF4 reduced colour (30%) and lignin content (24%) of the effluent on 3rd day. The fungal strain was identified as Emericella nidulans var. nidulans (anamorph: Aspergillus nidulans) on the basis of rDNA ITS1 and rDNA ITS2 region sequences. The process of decolourization was optimized by Taguchi approach. The optimum conditions were temperature (30–35°C), rpm (125), dextrose (0.25%), tryptone (0.1%), inoculum size (7.5%), pH (5) and duration (24h). Decolourization of effluent improved by 31% with reduction in colour (66.66%) and lignin (37%) after treatment by fungi in shake flask. Variation in pH from 6 to 5 had most significant effect on decolourization (71%) while variation in temperature from 30 to 35°C had no effect on the process. Treated effluent was further evaluated for geno-toxicity by alkaline single cell gel electrophoresis (SCGE) assay using Saccharomyces cerevisiae MTCC 36 as model organism, indicated 60% reduction. [Copyright &y& Elsevier]

Although microfluidic paper-based analytical devices (μPADs) get a lot of attention in the scientific literature, they rarely reach the level of commercialization. One possible reason for this is a lack of application of machine learning techniques supporting the design, optimization and fabrication of such devices. This work demonstrates the potential of two chemometric techniques including design of experiments (DoE) and digital image processing to support the production of μPADs. On the example of a simple colorimetric assay for isoniazid relying on the protonation equilibrium of methyl orange, the experimental conditions were optimized using a D-optimal design (DO) and the impact of multiple factors on the μPAD response was investigated. In addition, this work demonstrates the impact of automatic image processing on accelerating color value analysis and on minimizing errors caused by manual detection area selection. The employed algorithm is based on morphological recognition and allows the analysis of RGB (red, green, and blue) values in a repeatable way. In our belief, DoE and digital image processing methodologies are keys to overcome some of the remaining weaknesses in μPAD development to facilitate their future market entry. Image 1 • Optimization of device geometry and amount of assay reagent using D-optimal design. • Investigation of seven factors at three levels by only performing 44 trials. • MATLAB-based morphological recognition algorithm for signal readout. [ABSTRACT FROM AUTHOR]

• Adsorptive uptake of fluoride using novel paper industrial waste (PWA) was studied. • Fluoride removal process was optimized via RSM, ANN and GA. • PWA was characterized through SEM, EDX and FTIR. • Maximum removal of 99% was achieved by PWA. • 96.7% of fluoride removal achieved after four cycles of use of PWA. The current investigation emphasizes on the fluoride adsorption by chemically activated industrial paper waste (PWA) from aqueous medium. Sorption process was modelled and optimized using the techniques viz. response surface methodology (RSM), artificial neural network (ANN), and genetic algorithm (GA). Parametric effects of pH, adsorbate concentration, duration of contact, temperature, and PWA dose on percentage removal were assessed. Structural morphologies of PWA were analysed using BET, SEM, EDX and FTIR. Maximum removal of more than 99% was observed at adsorbate concentration of 12 mg/L, pH 5, temperature 25 °C and PWA dose 0.3 g/L and duration of contact of 18 h. The adsorption process conformed Langmuir isotherm model, and the process is thermodynamically feasible and spontaneous in nature as obtained from thermodynamics study. The PWA is reusable and capable of adsorbing 96.7% of total fluoride even after four cycles of use. Therefore, PWA might be a promising adsorbent for fluoride decontamination of water and can be used in sorption-based water treatment plant under optimised parametric condition to substantiate its large-scale applicability. [ABSTRACT FROM AUTHOR]

The performance of electrocoagulation (EC) using iron as sacrificial electrode was investigated at low current densities (0.6–1.9 mA/cm2) for treating a waste stream from a Kraft paper mill. A multi-level factorial design of experiments and response surface methodology (RSM) were applied to quantify the effects of current density and reaction time on the removal efficiency of color, COD, BOD 5 , tannin/lignin as well as on the enhancement of biodegradability index (BI). Increasing current density or reaction time significantly improve the treatment performance. An antagonistic effect of the two studied factors was identified, indicating that simultaneously increasing current density and reaction time does not yield added improvement in treatment performance. An RSM was developed to predict the optimum current density and reaction time within the experimental data range of this study. It was found that an optimized treatment combination exists at relatively low current density and reaction time. The optimum value for maximum pollutants removal was ∼1.5 mA/cm2 and ∼25 min. Under the optimum condition, the removals of tannin/lignin and color were >70 % and >95 %, and BI was increased to 0.41 BOD 5 /COD. Current density is the dominant factor for energy consumption and operating cost compared to reaction time and electrode consumption. This study demonstrated that EC can be operated at low current density to remove the bio-refractory organics effectively and increase the biodegradability index to the level suitable to biological treatment at low operating costs. [ABSTRACT FROM AUTHOR]

• Steam followed by alkaline treatment enhanced enzyme accessibility of PPS cellulose. • Reducing sugar yield was maximized during batch hydrolysis by optimized conditions. • High solid fed-batch hydrolysis was developed by ideal enzyme addition strategies. • Fed-batch S-SSCF with specified pre-hydrolysis was developed for high ethanol titer. The current study investigated an integrated fermentation process for efficient conversion of pulp and paper sludge (PPS) material to bio-ethanol. To achieve maximum yield of reducing sugar from the pretreated PPS, most influencing parameters such as enzyme dosages, surfactant dosages on PPS loadings were optimized in a batch saccharification process using response surface methodology. The experimental validation studies under optimal conditions of 6% (w/w) solid loading condition, 0.16% (w/w) of surfactant concentration and 158 FPU/gm of enzyme loading resulted in a maximum reducing sugar yield of 45 ± 3.75% (w/w). Separate batch saccharification studies were conducted with 4% to 7% (w/w) solid loading to formulate best operating conditions for fed-batch saccharification with 13% (w/w), 18% (w/w) and 22% (w/w) high solid loading. The PPS solid loading of 18% (w/w) in fed-batch saccharification resulted in maximal release of glucose and xylose of 79.56 g/L and 8.65 g/L respectively at 60 h. Further improvement in the conversion of PPS to bioethanol was established through adoption of fed-batch semi-simultaneous saccharification and co-fermentation (S-SSCF) process. Fermentation using co-cultivation of two yeast species namely P. stipitis NCIM 3499 and Baker's yeast resulted in maximum ethanol concentration of 42.34 g/L with 0.53 g/g yield from 18% (w/w) solid loading. Thus, the current study demonstrated the potential application of PPS waste as a feedstock material for ethanol production, which can be adopted by industries as an environment-friendly alternative to common solid waste management. [ABSTRACT FROM AUTHOR]

Highlights: [•] The addition of paper waste increases the thermal performance of bricks. [•] Paper waste additions into brick increase the porosity. [•] Predictive models for simulation and optimization of heat transfer process have been developed. [•] Material conductivity, surface emissivities and mean brick temperature have been considered as input variables. [•] The design of hollows in brick models helps further improve the thermal performance. [Copyright &y& Elsevier]

Highlights • First report on cellulase production by Bacillus velezensis using waste paper. • Pretreatment increased the cellulose content without any inhibitors formation. • Central composite design increased the cellulase production by three fold. • Cost-effective approach of waste management is achieved. Abstract This paper reports the cellulase (FPase) production by newly isolated Bacillus velezensis ASN1 using waste office paper (WOP) as feedstock and optimization of production conditions through two level factorial design, steepest ascent/descent and second order response surface methodology (RSM). Various fermentation parameters, like chemical factors (potassium dihydrogen phosphate, potassium chloride, yeast extract, magnesium sulphate, sodium nitrate, Tween 80, and waste office paper), physical factors (temperature, pH and time) and biological factor (inoculum size) were examined using two level full factorial design to check the key factors significantly affecting the cellulase production. The central composite design (CCD) was used to optimize the vital fermentation parameters, such as carbon (WOP), nitrogen, pH, and inoculum concentration in the medium for achieving higher cellulase production. The optimum medium composition was found to be WOP (9 g/L), sodium nitrate (0.35 g/L), inoculum size (6.56%) and pH 4.72. The model prediction of 2.46 U/mL cellulase activity at optimum conditions was verified experimentally as 2.42 U/mL. [ABSTRACT FROM AUTHOR]

Due to the huge amounts of wastewater discharge and the high pollution loads in papermaking industry, many greenhouse gases (GHG) are emitted in the papermaking wastewater treatment process. The wastewater dissolved oxygen (DO) control has been considered as the most cost-effective control solution for GHG reduction in wastewater treatment plants (WWTP). However, the competition between contaminant removal efficiency and GHG reduction hinders the drastic reduction of GHG emissions from WWTP. In this study, based on the established integrated GHG emission model, explicitly considering the total GHG reduction targets on the premise of effluent compliance, an intelligent control scheme has been developed for an activated sludge process in a paper mill. Regarding DO as the controlled variable, the proposed hierarchical optimal proportional-integral (HOPI) control scheme was established consisting of three layers: 1) Layer 1 for the effluent quality estimation, 2) Layer 2 for the optimal DO set point determined by genetic algorithm with the influent variations to obey discharging norms and reduce GHG emissions, 3) Layer 3 for the DO tracking proportional integral (PI) control with the controller parameters adjusted by the back propagation neural network to track the dynamically optimized DO set points. The simulation results showed that, compared with the open-loop (OL) operation (averaged aeration, 10/h), the proposed HOPI control (averaged aeration, 7.9/h) reduced the GHG emissions by 12.54% under the premise of discharging norms, which was mainly attributed to the reduction of the aeration electricity consumption. In contrast, the PI control (averaged aeration, 12.9/h) increased the GHG emissions by 7.48% compared with the OL operation. Thus, the proposed HOPI control strategy has demonstrated potential for the application of GHG reduction in industrial WWTPs. [ABSTRACT FROM AUTHOR]

The design of a high-volume printer for professional use is rather complex. The design of the paper path and the timing of sheets is frequently reengineered as the design of the printer components progresses. This paper presents an optimization model for the combined paper path and timing design problem. The paper path is an optimal physical dimensioning problem, while the timing is an open-loop optimal control problem. The coupled optimization problem is formulated as a simultaneous analysis and design (SAND) problem using a direct transcription of the optimal control problem. Benefits of the chosen formulation for industrial application are the ease of setting up the optimization model for arbitrary printer configurations, and the short computation times. Results of an industrial case are presented. [ABSTRACT FROM AUTHOR]

This paper presents a MILP (Mixed Integer Linear Programming) model for a continuous packed-bed biomass dryer. The model minimizes total drying costs, including both capital and operational costs, of the dryer. Heated air, which flows through a biomass bed and perforated conveyor, is used as drying gas by the dryer. We define the dryer size with the help of an experimentally-measured characteristic drying curve. The MILP model is tested in a case study where the dryer is assumed to have been installed at a Scandinavian pulp and paper mill. There are three different heat sources available for the heating of drying air: warm water at 60 °C, warm water at 80 °C and backpressure steam at the pressure of 0.4 MPa. The results indicate that, in practice, the use of only low-temperature warm water flows for heating of drying air is the most economic method when their prices are low (below 1 € MWh −1 in the case study). Warm water flows are usually waste heat from pulp and paper mills and their prices are low compared to the price of back-pressure steam (typically from 10 to 15 € MWh −1 ). The use of steam for drying may be reasonable if the price of warm water is for some reason clearly higher than the price of a typical waste-heat stream. The MILP model presented in this work can be used for minimizing drying costs of any material (not only biomass) dried in a continuous packed-bed dryer if the characteristic drying curve of the material is available. [ABSTRACT FROM AUTHOR]

Abstract: Energy conservation is a central concern of the current industrial world, where increasing efficient energy usage is the only way of reducing a high energy demand. In the present study the optimization of a pulp and paper mill with a cogeneration plant has been carried out. The optimization was realized with a methodology which includes exergy, exergoeconomics, thermoeconomics and pinch analysis. The proposed methodology was useful in determining not only the best plant operating conditions but also establishing the components or subsystems with the highest irreversibilities. As a result of the study, operation changes in the recovery boiler, the turbogenerator, the thermal treatment and the deaerator were realized. Due to the higher irreversibility in the actual evaporator line, a new line of evaporators was proposed. Also, an innovative heat recycling technology as to the use of heat transformers was proposed in order to reduce waste heat discharged to the atmosphere. The results obtained with the proposed methodology, which integrates the different optimization methods, allowed reaching higher efficiencies and lower operational costs than those obtained with the optimization methods working separately. [Copyright &y& Elsevier]

Abstract: Three fungal strains were isolated from sediments of pulp and paper mill in which PF7 reduced colour (27%) and lignin content (24%) of the effluent on 5th day. PF7 was identified as Cryptococcus sp. isolate FIST3 on the basis of ITS1 and ITS2 region sequences. The process of decolourization optimized, in shake flask experiments, by Taguchi approach indicated optimum conditions: temperature (30–35°C); shaking condition (125rpm); dextrose (1.0% w/v); tryptone (0.1% w/v); inoculum size (7.5% w/v); pH (5) and duration (24h). Overall evaluation criterion (OEC) value before optimization was 32.3. There was 38% improvement in the process with final OEC value, 44.6±2.02, at optimum conditions. The colour content of the effluent reduced by 50–53% and lignin content 35–40% after treatment at optimum conditions. Variation in pH from 5 to 6 had most significant effect on decolourization (72%) while variation in temperature from 30°C to 35°C had no effect on the process. Treated effluent was further evaluated for toxicity by alkaline single cell (comet) gel electrophoresis (SCGE) assay using Saccharomyces cerevisiae MTCC 36 as model organism, indicated 45% reduction. The results showed significant reduction in colour, lignin and toxicity of the effluent and this process can be scale up to industrial level. [Copyright &y& Elsevier]

Abstract: The heat recovery system (HRS) is a vital part in a paper machine when it comes to the overall energy economy in papermaking. For a typical newsprint machine more than 60% of the exhaust energy from the dryer section can be recovered, resulting typically in a regain of about 30MW. The synthesis task of a HRS is a decision process where the target is on the one hand to achieve maximal energy recovery and on the other hand to obtain it with minimal investment costs. These goals are contradictory and thus the problem is to find a solution minimizing the overall costs, considering simultaneously both energy and investment costs. One further challenge is how to take into account known variations in the parameters so that the design is robust, i.e. it is capable of handling all evolving situations and furthermore the design should be the most economical one when also considering the duration of all expected operational situations. In this work a hybrid method based on evolutionary programming and non-linear programming for the synthesis of robust and optimal heat recovery systems (HRS) for paper machines is presented. Variations and uncertainties on process parameters are modeled with probability distributions and the cost of the utilities are thus obtained as an integrated value of all different situations expected to evolve. The importance of obtaining a robust design is shown in a case study. [Copyright &y& Elsevier]

Paper microfluidic or lateral flow devices have found many applications, especially in medical diagnostics. Their low cost and ease of use makes them particularly valuable in resource-limited and point-of-care applications. However, the process of developing new paper microfluidic devices is slowed by the need to find optimal values for their various design parameters, which determine the overall size and fluid volume requirements of the device. Often, researchers must design and test several different versions of a device to find a combination of parameters that functions as intended. To accelerate the development of new paper microfluidics, we developed a software framework that automatically designs custom paper microfluidic devices for a given application. Once the user specifies the desired device parameters, the software generates printable image files of the resulting devices, ready to output to a conventional wax ink color printer and test. As a proof-of-concept, we used our software to automatically design 51 different paper microfluidic devices we needed to create a functional lateral flow assay that detects protein and glucose in urine. These designs took only a few seconds to generate and were used in 120 lab experiments we performed in 16 h in the lab. Thus, with the help of our software framework, we went from an idea to a functional device in just two work days. By accelerating device development and enabling researchers without microfluidics experience to create custom devices, our software can help spread paper microfluidic technology to important new application areas. [Display omitted] • Software can automatically generate custom paper microfluidic device designs for a given application. • In just a few seconds, our software generated all 51 device designs we needed to develop a urinalysis assay. • This software enabled us to go from an idea to a functioning paper microfluidic device in just two days in the lab. [ABSTRACT FROM AUTHOR]

Lactic acid promises to be an important commodity chemical in the future as a monomer for the production of biodegradable polylactic acid. With the increase of the lactic acid demand, the need to explore alternative feedstock sources and purification processes that are inexpensive and efficient is becoming more important. This paper first reports the purification results of lactic acid from the fermentation broth with paper sludge as a cellulosic feedstock using weak anion exchanger Amberlite IRA-92. Some factors such as flow rate, sample volume loaded, pH, and column were systematically examined to improve the purity, yield and productivity in lactic acid purification. Adsorption isotherm of standard lactic acid and lactic acid in the fermentation broth by anion exchanger IRA-92 were also investigated. Results indicate that in purification process the increase of pH of the fermentation broth ranging from 5.0 to 6.0 can significantly enhance the recovery yield, purity and productivity. The decrease of flow rate and sample volume loaded can also improve the recovery yield and purity but apparently reduce the productivity. In addition, the scale-up of purification process in laboratory size has little influence on the recovery yield and purity. After optimization, the yield, purity and productivity are found to be about 82.6%, 96.2% and 1.16 g LA/(g-resin day), respectively. [Copyright &y& Elsevier]

Abstract: Availability analysis has been an important issue in the design field of any Industrial system as the system structure has become more complicated. Also, the system availability is affected by many factors such as design, manufacturing, installation, etc., and so it may be extremely difficult to model, analyze and predict the failure behavior of the system. The purpose of this paper is to develop a new approach for computing various performance measures, namely reliability, availability, MTBF (mean time between failures), ENOF (expected number of failures), failure rate and repair time, for any industrial system. In the proposed approach, the failure rates and repair times of all constituent components are obtained using genetic algorithms and then various performance measures are computed using fuzzy lambda–tau methodology. Washing system, the major part of paper industry is the subject of study. The interactions among the working components are modeled using Petri nets. Failure and repair rates are represented using triangular fuzzy numbers as they allow expert opinion, linguistic variables, operating conditions, uncertainty and imprecision in reliability information to be incorporated into system model. Based on calculated reliability parameters, a structured framework has been developed that may help the maintenance engineers to analyze and predict the system behavior. [Copyright &y& Elsevier]

This paper introduces a new approach for improving the performance and versatility of Layered Manufacturing (LM), which is an emerging technology that makes it possible to build physical prototypes of 3D parts directly from their computer models using a “3D printer” attached to a personal computer.Current LM processes work by viewing the computer model as a single, monolithic unit. By contrast, the approach proposed here decomposes the model into a small number of pieces, by intersecting it with a suitably chosen plane, builds each piece separately using LM, and then glues the pieces together to obtain the physical prototype. This approach allows large models to be built quickly in parallel. Furthermore, it is very efficient in its use of so-called support structures that are generated by the LM process.This paper presents the first provably correct and efficient geometric algorithms to decompose polyhedral models so that the support requirements (support volume and area of contact) are minimized. Algorithms based on the plane-sweep paradigm are first given for convex polyhedra. These algorithms run in O(nlogn) time for n-vertex convex polyhedra and work by generating expressions for the support volume and contact-area as a function of the height of the sweep plane, and optimizing them during the sweep. These algorithms are then generalized to non-convex polyhedra, which are considerably more difficult due to the complex structure of the supports. It is shown that, surprisingly, non-convex polyhedra can be handled by first identifying certain critical facets using a technique called cylindrical decomposition, and then applying the algorithm for convex polyhedra to these critical facets. The resulting algorithms run in O(n2logn) time. Also given is a method for controlling the size of the decomposition, so that the number of pieces generated is within a user-specified limit. Experimental results show that the proposed approach can achieve significant reduction in support requirements in both the convex and the non-convex case. [Copyright &y& Elsevier]

Highlights • Agave tequilana bagasse was pretreated with 1-ethyl-3-methylimidazolium acetate. • Biomass loading, reaction time and temperature conditions were optimized. • High sugar yield was achieved at milder conditions than those previously reported. • Solid recovery after pretreatment was a key factor for improving sugar yield. • Saccharification was improved by decreasing crystallinity and lignin content. Abstract Sequential 2k factorial and central composite designs were used to optimize Agave tequilana bagasse (ATB) pretreatment by using 1-ethyl-3-methylimidazolium acetate ([Emim][OAc]). Reaction time, temperature and solids loading were the studied factors while sugar yield was the response variable. Results indicated that optimal conditions (119 °C, 142 min) using high solids loading (30%) were achieved at lower temperatures and reaction times than those previously reported in the literature. It was also revealed that solid recovery after pretreatment with [Emim][OAc] is a key factor. The increase in enzymatic digestibility of pretreated ATB was correlated to a decrease in crystallinity and lower lignin content as observed using microscopy techniques and weaken chemical bonds by Fourier transform infrared spectroscopy. Yields of glucose and xylose in the hydrolysate were 41.3, and 13.0 kg per 100 kg of untreated ATB, which are equivalent to glucan and xylan conversions of 75.9% and 82.9%, respectively. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we study the heat transfer and fluid flow in a step-down 3-phase power transformer. In order to simplify the study we choose an element composed of two windings wound around a core. The Joule effect and the Foucault currents produce an undesirable heat in the different components of the transformer. From an economical and security point of view, there is a need to cool the transformer to preserve it from destruction. Our main objective is the cooling optimization of the power transformer. In order to attain this goal, a numerical study has been conducted for six different geometric configurations with six different flow rates of the cooling oil at the entrance. The physical properties of the fluid are supposed to be function of the temperature. The control volume method has been used to resolve the continuity, the momentum and the energy equations in the steady state. The obtained results show that the structure of the flow is somehow complex and according to the case some rolls appear at the top and the bottom of the windings, these rolls contribute to a good mixing of the fluid leading to a nearly homogeneous temperature. [Copyright &y& Elsevier]

Abstract: Plating bath concentrations of Pt(IV) and Ir(III) have been optimized as well as the total catalytic loading of bimetallic Pt–Ir alloy for the electro-oxidation of ammonia in alkaline media at standard conditions. This was accomplished using cyclic voltammetry, scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and statistical optimization tools. Concentrations of Pt(IV) and Ir(III) of the plating bath strongly influence electrode surface atomic compositions of the Pt–Ir alloy directly affecting the electro-oxidation behavior of ammonia. Several anode materials were studied using cyclic voltammetry, which demonstrated that Pt–Ir was the most active catalyst for the electro-oxidation of ammonia. Criteria for optimization were minimizing the climatic oxidation overpotential for ammonia and maximizing the exchange current density. Optimized bath composition was found to be 8.844±0.001gL−1 Pt(IV) and 4.112±0.001gL−1 Ir(III) based on electrochemical techniques. Physical characterization of the electrodes by SEM indicates that the plating bath concentrations of Pt and Ir influence the growth and deposition behavior of the alloy. [Copyright &y& Elsevier]

Abstract: The overproduce-and-choose strategy, which is divided into the overproduction and selection phases, has traditionally focused on finding the most accurate subset of classifiers at the selection phase, and using it to predict the class of all the samples in the test data set. It is therefore, a static classifier ensemble selection strategy. In this paper, we propose a dynamic overproduce-and-choose strategy which combines optimization and dynamic selection in a two-level selection phase to allow the selection of the most confident subset of classifiers to label each test sample individually. The optimization level is intended to generate a population of highly accurate candidate classifier ensembles, while the dynamic selection level applies measures of confidence to reveal the candidate ensemble with the highest degree of confidence in the current decision. Experimental results conducted to compare the proposed method to a static overproduce-and-choose strategy and a classical dynamic classifier selection approach demonstrate that our method outperforms both these selection-based methods, and is also more efficient in terms of performance than combining the decisions of all classifiers in the initial pool. [Copyright &y& Elsevier]

Snake robots have redundant kinematic structure which predetermines them for motion in rough and unstructured terrain with obstacles, narrow spaces or environments with different ground levels. Dynamic modeling of snake robots is an important element in the development of control strategies for them. This paper, deals with the dynamic model of a snake robot moving in a pipeline. The model is based on Newton's mechanics with consideration of the viscous as well as Coulomb friction model. The paper uses Hertz theory for modeling of contact between a snake robot and side walls of a pipeline. Based on optimization process results, the friction effects as well as analyses of snake robot propulsive force are investigated. The main contributions of the paper are the developed dynamic model for snake robot motion in a pipeline, open source code of the developed model in MATLAB, and analyses of individual parameters of snake robot motion. • Propulsive force of snake robot moving in a pipeline is significantly affected by friction of the side walls. • One full sine wave formed by snake robot links ensures maximum average velocity. • Considering Coulomb friction the snake robot performs more jerked motion in comparison with viscous friction. [ABSTRACT FROM AUTHOR]

Ammonia production has traditionally been done by using the Haber-Bosch process, that operates at extremely high pressure (200–300 bar), has a large carbon footprint, and requires significant energy. For ammonia to be used as a hydrogen carrier, it is desired that it is produced by using modular technologies under benign conditions, yet the economics remain commercially viable. This paper investigates a novel technology for ammonia synthesis by using a microwave-assisted low-pressure reactor. Microwave reactors are compact and can be readily modularized and started/shutdown thus making them ideal to be integrated with the electric grid or with regional/local renewable-based electric generation facilities. For separation of unreacted reactants from the product ammonia, if the traditional condensation separation technology used in the high-pressure Haber-Bosch process is used, then the separation process needs to be operated under cryogenic condition thus adversely affecting the economics. A solid sorbent based separation technology is investigated in this paper. A kinetic model for the microwave-catalytic synthesis process is used. An isotherm model is developed for MgCl 2 –Si adsorbent and used for modeling the dynamic adsorption-desorption cycle. A plant-wide model with heat and mass integration is developed. An economic model is developed and used for economic optimization by using an equation-oriented approach. Since the adsorption-desorption process is dynamic, for techno-economic optimization, a reduced order model for the key performance measures of the adsorption-desorption process as a function of its input and decision variable is developed under cyclic steady-state conditions. For the optimized MW-assisted process, the levelized cost of ammonia is $772/mt as opposed to $808/mt for the conventional Haber-Bosch process for a hydrogen price of $2.07/kg. The MW-assisted process is found to be economically viable in the US market if the hydrogen price is below $4/kg. • Plant-wide model of a novel MW-assisted ammonia synthesis process is developed. • A solid-sorbent based separation technology is investigated for separation. • A reduced model based approach is developed for optimizing the adsorption process. • For the optimized process, the levelized cost of ammonia is found to be $772/mt. • The technology is found to be economically viable for H 2 price below $4/kg. [ABSTRACT FROM AUTHOR]

A novel mathematical modeling approach for the Triple-Diode Model (TDM) and its parameter estimation is introduced in this paper. For the first time in the literature, this paper presents two analytical solutions for calculating the current in TDM solar cells using the Lambert W function. Additionally, a new metaheuristic algorithm, the Adaptive Evaporation Rate Water Cycle Algorithm (Adaptive ERWCA), is proposed for estimating TDM solar cell parameters. The proposed algorithm is tested using both the new analytical solutions and a well-known iterative approach for the current-voltage characteristics of the TDM solar cells model. Extensive testing is conducted on three well-known solar cells/modules and a panel under various weather conditions. The results demonstrate that the proposed analytical expressions for the current-voltage characteristics are accurate and highly effective for representing TDM solar cell current. The accuracy of the parameter estimates obtained with the application of the proposed algorithm, considering both analytical solutions and the iterative approach, is compared with existing literature results. It is shown that the proposed algorithm outperforms existing algorithms in solar cell parameter estimation across both the analytical and iterative approaches for current-voltage characteristics. Remarkably, for the RTC France solar cell, the SOLAREX MSX 60 solar module, and the PHOTOWATT-PWP 201 solar module, the obtained Root Mean Square Errors (RMSE) are 0.00075141, 0.01157153, and 0.0010578, respectively. These results are currently the best reported in the literature. [ABSTRACT FROM AUTHOR]

Comet Interceptor (Comet-I) was selected in June 2019 as the first ESA F-Class mission and aims to explore a pristine comet, which will visit the inner Solar System for the first time. Comet-I will hitch a ride to a Sun-Earth L2 quasi-halo orbit, as a co-passenger in ESA's M4 ARIEL's launch. At the time of writing, this is scheduled for 2029. It will then remain there awaiting the right departure conditions to leave definitively and intercept a newly discovered comet. Comet-I will be the first mission to be designed and launched without an already identified target. Given the latter, the Comet-I Target Identification Working Group is tasked with the continuous follow-up of newly discovered comets, to analyse their characteristics as virtual targets for Comet-I. The goal of the paper is to inform the decision-making process that will eventually be necessary to commit Comet-I spacecraft to its final target. Within this context, this paper presents a trajectory optimization process based on Primer Vector theory that considers intercept trajectories with multiple revolutions and multiple deep space manoeuvres (DSM). The process is applied to 21 long period comets, which were discovered since July 1, 2020 and whose characteristics are of interest for the Comet-I mission. In fact, one of the latest of these recently discovered comets, C/2023H2, is the most accessible virtual target discovered at the time of writing, with delta-V intercept costs well within Comet-I capabilities. A complete launch window analysis is thus presented for C/2023H2, which accounts not only for the most optimal delta-V intercept transfer, but also considers all launch options that satisfy all Comet-I's current boundary conditions and flyby constraints. A systematic launch window analysis is made possible by a grid search approach on which departure and fly-by dates are fixed and the remaining design variables, including the times for manoeuvres and their Δ v impulse vector, are optimized via Primer Vector theory. This allows to understand the latest possible departure date, but also the sensitivity to departure and arrival dates of key encounter characteristics such as relative fly-by speed, the solar aspect angle and the Earth distance. • A Primer Vector Theory-based trajectory optimization tool is shown, tailored for ESA's Comet Interceptor (Comet-I). • The method supports trajectories with multiple revolutions around the Sun and multiple impulses. • The method allows rapid grid search over the search space, finding the lowest cost trajectory and other notable solutions. • A novel analysis of the launch window is presented, contributing to the decision-making process of Comet-I. • A multi-manoeuvre strategy benefits Comet-I's trajectory design, lowering the delta-V cost and improving mission flexibility. [ABSTRACT FROM AUTHOR]

Abstract: In the present work a number of configurations and difficulties of MEE system such as condensate flashing, vapor bleeding, steam splitting, preheating of liquor using condensate, variable physical properties and boiling point rise are taken into consideration to analyze the evaporation system. For this purpose seven effect evaporator system of a typical Indian pulp and paper industry is considered. The model developed is a set of nonlinear algebraic equations that include total and solute mass balances, energy balances, heat transfer rate equations, and the composition and temperature dependence of thermodynamic properties such as vapor pressures and enthalpies. The model is solved using nonlinear equation solver. Economic evaluation to optimize the number of flash tanks is carried out for seven effect evaporator system. The two different types of configurations of vapor bleeding are considered and compared. Considering optimum number of flash tanks and best configuration of vapor bleeding, a system is designed. Further, a modified system is found considering optimum number of flash tanks and preheating of liquor using condensate. This modified design enhances the steam economy by 23.77% and reduces the steam consumption by 36.76% in comparison to base case and thus, it is selected as optimum design. Finally, Pinch analysis of the MEE network has also been carried out and it is found that predicted results are compared well with base case. [Copyright &y& Elsevier]

Locomotive engines serve as the powering heart of rail transportation which is widely used for massive cargo over long distances. The traditional locomotive engines have depended on the internal combustion engine for decades, operated using fossil fuels that negatively impact the environment. Since more and more commodities are transported by trains, the prime engines need to be improved where the fuels are expected to enhance the engine's performance and alleviate the environmental impact. This paper presents a comparison of three developed locomotive engines with different configurations, such as an internal combustion engine combined with a gas turbine and molten carbonate fuel cell (ICE-GT-MCFC), a gas turbine combined with a solid oxide fuel cell and onboard hydrogen production using aluminum electrolysis cell (GT-SOFC), and a GT combined with sold oxide and proton exchange membrane fuel cells (GT–SOFC–PEMFC). The paper then identifies one hybridized engine, which is GT–SOFC–PEMFC, according to its low weight and better performance to conduct an optimization study to enhance its efficiency, reduce the cost, and lower the environmental impact. The present optimization study is undertaken through a multi-objective particle swarm optimization, involving thermodynamic, exergoeconomic, and exergoenvironmental analyses. The optimized GT–SOFC–PEMFC locomotive engine is improved in power from 5.9 MW to 7.3 MW and improved in performance to 49.1% energetic efficiency and 47.0% exergetic efficiency. Additionally, the optimized GT–SOFC–PEMFC engine has less specific fuel and product cost of 24.9 $/GJ and 34.7 $/GJ, respectively, and less specific exergetic environmental impact of fuel and product of 13.2 Pt/GJ and 16.2 Pt/GJ, respectively. Also, the relative cost difference and relative environmental impact difference are significantly reduced by more than 20% to 39.4% and 22.8%, respectively. The operational conditions of the optimized GT–SOFC–PEMFC engine are improved to achieve better efficiency and better cost effectiveness in a more environmentally-benign manner. • Comparison between three hybridized combined locomotive engines is established. • Optimized GT–SOFC–PEMFC engine has 7.3 MW power and 49% energetic efficiency. • Specific exergetic product cost declined to 51 $/GJ for fuel and 35 $/GJ. • Specific exergetic environmental impact for fuel and product becomes 13 and 16 Pt/GJ. • The relative environmental impact difference becomes 22.8% instead of 44.3%. [ABSTRACT FROM AUTHOR]

In a construction environment, project scheduling is an essential tool to measure the success of all projects. This research paper will use project crashing of Activity to decrease the project completion schedule through the CPM method of time-cost trade-off and to minimize project cost. It includes linear programming with the aid of Microsoft Excel Solver to determine the result. And at the end of the research paper, it will show the impact of crashing the activities for the HVAC mechanical installation in a project for both normal and crash time, which displays that the selected Activity that had been crashed generated an increase of 9.8 % total cost from the total project cost. [ABSTRACT FROM AUTHOR]

• A review of waste management optimization models (WM-OMs). 2. • A novel characterization method for examining and benchmarking the features WM-OMs. 3. • A pioneering guide for the selection of proper uncertainty analysis approaches. 4. • A compilation of characteristics of the papers reviewed and their data (Appendix). 5. • A perspective on the design of WM-OMs for different applications and stakeholders. 6. The transition to a circular economy through sustainable waste management (WM) follows different paths in each region, depending on its socioeconomic conditions and existing infrastructure. Mathematical optimization models are rigorous tools for informing local decision-making and identifying WM policy levers based on a variety of configurations. This review explores the pathways taken when designing WM optimization models (WM-OMs) that establish a network of waste valorization technologies. To standardize the literature review process, we propose a novel characterization method for examining, relating, and benchmarking the features of WM-OMs. After a thorough review of 58 articles published between 2015 and 2022, we assembled a comprehensive database to document the characteristics of these papers and the type of data reported in their case studies. We aim to provide a solid foundation for streamlining and enhancing future WM-OMs. Our work identifies various opportunities to improve the accuracy and reliability of WM-OMs. They include modeling thermo-chemical reactions in WM processes; considering regulatory, environmental, and political constraints; recognizing the informal sector; exploring the impact of marketing mechanisms on waste prevention and recycling; improving the traceability of case study data; specifying the rationale for uncertainty analysis (UA); and indicating the mathematical model (type, optimization algorithm, and equations). As many WM-OM authors have implemented UA without justifying their method choices, our review provides a pioneering guide for selecting the UA approach. Finally, we discuss the need for a trade-off between performance and practicality as models become more complex, making it critical to consider the specific needs of stakeholders. [ABSTRACT FROM AUTHOR]

This paper introduces a novel application of neural style transfer to video sequences, leveraging pre-trained Convolutional Neural Network (CNN) models. By combining content and style losses in an optimization process, the approach transforms video frames into visually captivating compositions, opening new avenues for artistic expression in visual storytelling and filmmaking. The procedure begins with meticulous preprocessing of video frames to align them with the specifications of the powerful VGG16 model. A content model is then constructed to extract activations from the 14th layer of the VGG network, forming the groundwork for nuanced content depiction. Style information is computed by aggregating data from a combination of convolutional layers, resulting in a multifaceted, artistically complex tapestry. The paper introduces a well-balanced loss function that combines style and content losses, serving as the foundation for the ensuing optimization procedure. This careful balancing between style adherence and content authenticity yields visually stunning synthesis, enhancing video sequence quality and artistic resonance. The paper also delves into a detailed analysis of hyper parameters, particularly style weights, and introduces a novel pixel value scaling method for enhanced visual coherence. Experimental findings demonstrate the efficiency and adaptability of the proposed approach, showcasing the seamless integration of content and style for an immersive visual experience. This accomplishment marks a significant stride toward unlocking the creative potential of video content, ushering in a period of enhanced visual storytelling. [ABSTRACT FROM AUTHOR]

Brain stroke is one of the most common causes of disability and death worldwide. In this paper, we present the numerical algorithm behind a new system for brain stroke detection: it relies on a novel imaging technique known as Electromagnetic Tomography (EMT). As compared to classical techniques, EMT has several advantages: it is noninvasive and, since it relies on nonionizing radiation, it is safe for the patient; it can be made compact and portable; it is easy to use and it has relatively low cost. The main drawback of EMT is its relatively poor spatial resolution due to restriction on the frequency spectrum. This paper describes the numerical challenges we had to overcome when designing our latest generation scanner. [ABSTRACT FROM AUTHOR]

This paper investigates an intelligent strut design scheme for achieving high-performance combustion of a combustion chamber under wide-ranging flow conditions. The design process involves optimizing the base strut configuration for the design point and obtaining the Pareto front. The subsequent selection of the optimal configuration is followed by analyzing and interpreting the optimization results using single-factor analysis rules. The findings reveal that the selected optimal configuration enhances the combustion efficiency by 8.22% and reduces the force by 66.12% compared to the traditional DLR combustion chamber. Additionally, a surrogate model is constructed to investigate the influence of the rotation angle of the intelligent strut's rotating blades on the combustion efficiency and force at a Mach number range of 2–3.5. Results indicate that the intelligent strut is capable of improving combustion efficiency via regulation, and the efficiency can quickly reach a desirable level. These findings suggest that the proposed design scheme has potential applications in achieving high-performance combustion in combustion chambers exposed to wide-ranging flow conditions. • This paper investigates an intelligent strut design scheme for achieving high performance combustion. • The design process involves optimizing the base strut configuration for the design point and obtaining the Pareto front. • This design scheme aims to achieve the best comprehensive combustion. Performance based on the design point. • Results indicate that the intelligent strut is capable of improving combustion efficiency. via regulation. [ABSTRACT FROM AUTHOR]

Since the machining of complex aerospace components, like integral compressor-rotors (blade integrated disks), is very cost-intensive, optimizing the process by means of process simulations is an active field of research. With the rise of Quantum Computing, a new instrument with high optimization potential is moving into focus. In this paper, a possible application of Quantum Computing for the machining simulation of multiaxis milling of thin-walled aerospace components is discussed. For this reason, a simulation framework used for the milling simulation is analyzed and each component is evaluated separately in relation to Quantum Computing. Parts of the Harrow, Hassidim, and Lloyd algorithm are proposed to enhance the Finite-Element simulation-based component, like the modal analysis for dynamics simulation. This algorithm can solve linear system problems with exponential speed-up over the classical method. The paper presents a roadmap on how the classical steps of a modal analysis for dynamics simulation could be replaced by quantum algorithms based on quantum phase estimation. The implementation of the first working steps is presented to validate this approach. The linear system problem, arising from the dynamics simulation, is analyzed in detail and a minimal value problem of linear coupled oscillators is derived. [ABSTRACT FROM AUTHOR]

Static mixer studies in literature have often been reported for idealized systems with a concentric injected flow. These do not account for real-world mixing scenarios where the additive comes in through an injector. Depending on the injector geometry, the injected flow, and pipe Reynolds number, the injected flow may end up off-centered. This impacts the static mixer performance as the first few elements are unable to provide efficient mixing. This paper discusses a parametric study of twisted-tape mixers to numerically ascertain their performance for Newtonian flows. It focuses on industrially relevant mixers which operate with some inexactness, e.g., off-center flow of the additive. Effect on mixing of angle of twist and aspect ratio of the individual element along with Reynolds number are studied; and the Reynolds number dependency of mixer geometry for optimal performance is established. This is done without using some oft-used approximations/assumptions in previous literature like zero-thickness mixer walls, 2d analysis, periodic boundary conditions etc. Two non-dimensional quantities, i.e., Coefficient of Variation (CoV) and Z -factor, are used to assess and quantify the operation of the mixers. For idealized systems, increasing the number of elements by reducing the aspect ratio and/or the twist angle is seen to improve mixing for all Reynolds numbers tested (1−100). However, for a real-world mixer constrained by its total length/pressure drop, mixing is proven to be an optimization problem between increasing the number of flow-splits by introducing a greater number of elements and mitigating the anomalous flow (uneven split) caused due to it. For Re ≤ 10, reduction of twist angle from 180∘ to 140∘ improves mixing for only aspect ratios greater than approximately 0.9. For Reynolds number of 100, the 140∘ twist angle outperforms the 180∘ twist angle for all aspect ratios studied. In summary, there is no combination of twist angle and aspect ratio that is a universally optimal solution and these parameters must be decided subjectively based on multiple other input parameters for a given system. • Optimizes the mixer geometry for non-ideal conditions found in manufacturing units. • Establishes a parameter space for twisted tape mixers in terms of Reynolds number, aspect ratio, and twist angle. • Input variables are studied in conjunction with each other instead of in isolation. • Demonstrates the necessity of system-level study, analysis, and optimization of twisted tape mixers. • Concludes that there is no universally applicable or "silver-bullet" geometry that is optimal for all input conditions. [ABSTRACT FROM AUTHOR]