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In this study, three variants of strain smoothing technique, viz. the cell-based, edge-based, and node-based smoothed finite element method, are employed for structural topology optimization. The salient features of the strain smoothing technique are: (i) does not require an explicit form of shape functions and (ii) less sensitive to mesh distortion. Within the proposed framework, the structural materials are modelled as the relative material density powered by the power-law approach. An optimum structural topology is estimated from the condition that minimizes the total strain energy of the structures of interest. The efficacy and the robustness of the strain smoothing technique, when applied to topology optimization, are demonstrated with a few standard benchmark problems. A systematic parametric study is done to find suitable and optimal control parameters for the topology optimization, viz. filter size, tuning parameter, and move limit. The relative performance of different strain smoothing techniques for structural topology optimization is also presented.

이 연구의 주요 목적은 콘크리트에 매입된 철근의 부식이 심화됨에 따라 철근-콘크리트 계면에서 철근 부식물질의 확산이 지배하는 상태에서 철근콘크리트 재료의 교류임피던스 특성을 해석 및 실험적방법을 통하여 이해하는 것이다. 이를 통하여 교류임피던스 측정을 활용한 철근부식 평가 방법의 현장적용성 향상을 위한 근사법을 제안하였다. 부식물질의 확산에 따른 교류임피던스 변화를 모델링하기 위하여 바버그 임피던스(Warburg impedance)를 고려한 전기등가회로 모델을 활용하였다. 시뮬레이션에서 얻은 결과는 이 연구에서 수행한 실험연구 결과와 비교함으로서 검증하였다. 이를 통하여 전하이동율속 및 확산율속 상태에서 10kHz 및 10mHz에서 측정한 교류임피던스 값은 철근-콘크리트계면에서 각각 용액저항 및 전하이동저항에 대응하는 임피던스 값의 실용적 관점에서 합리적인 추정치를 제공하는 것을 확인하였다. 이 연구에서는 최적주파수(10kHz 및 10mHz)를 활용한 2점 측정 방식으로 철근의 부식속도를 평가하였다. 측정된 분극저항값의 변화는 전 주파수 대역의 주파수스윕(frequency sweep)을 통하여 결정된 값, OCV(Open Circuit Voltage) 및 질량감소와 비교하여 타당성 검토를 하였다.

This research presents a case study on the remediation of a radioactive waste (uranium: U) utilizing a multi-objective fuzzy optimization in an electrocoagulation process for the iron-stainless steel and aluminum-stainless steel anode/cathode systems. The incorporation of the cumulative uncertainty of result, operational cost and energy consumption are essential key elements in determining the feasibility of the developed model equations in satisfying specific maximum contaminant level (MCL) required by stringent environmental regulations worldwide. Pareto-optimal solutions showed that the iron system (0 μg/L U: 492 USD/g-U) outperformed the aluminum system (96 μg/L U: 747 USD/g-U) in terms of the retained uranium concentration and energy consumption. Thus, the iron system was further carried out in a multi-objective analysis due to its feasibility in satisfying various uranium standard regulatory limits. Based on the 30 μg/L MCL, the decision-making process via fuzzy logic showed an overall satisfaction of 6.1% at a treatment time and current density of 101.6 min and 59.9 mA/cm2, respectively. The fuzzy optimal solution reveals the following: uranium concentration – 5 μg/L, cumulative uncertainty – 25 μg/L, energy consumption – 461.7 kWh/g-U and operational cost based on electricity cost in the United States – 60.0 USD/g-U, South Korea – 55.4 USD/g-U and Finland – 78.5 USD/g-U.

The primary purposes of this study are to investigate the feasibility of electrochemical deposition treatment (EDT) as a comprehensive rehabilitation method for corrosion-induced deterioration in reinforced concrete with various severity levels, and to propose a guideline for the determination of critical factors to advance EDT. This study includes three experimental phases, each of which simulates the initiation (de-passivation), propagation (high corrosion activity), and acceleration (formation of a surface-breaking crack) periods of corrosion-induced deterioration. After completion of a series of accelerated corrosion tests, damaged concrete samples with different severity levels are rehabilitated by a series of EDT processes using a MgCl2 solution in an electrolyte. The main variables for this experiment are the concentration levels (0, 0.3, 1.0 and 3.0 M) of a MgCl2 solution for test phase 1, charging time (0, 2, and 7 days) in EDT for test phase 2, and configuration of pre- and post-treatment processes in EDT for test phase 3. The rehabilitation performance of EDT is evaluated by analyzing the AC impedance properties of the steel-and-concrete interface using electrochemical impedance spectroscopy (EIS) for the test phases 1 and 2, and microscopic alternation in concrete cracks using optical microscopic image and SEM/EDX. It is demonstrated that EDT is an effective method for preventing and mitigating corrosion-induced deterioration in the initiation and rust propagation periods of corrosion and for repairing (closing and filling) a corrosion-induced surface-breaking crack in the acceleration phase of corrosion. Corrosion-resistant performance of concrete increases as the concentration levels of a MgCl2 solution in an electrolyte increases and as the charging time in EDT increases. In addition, a post-treatment process (applying a NaOH solution) after the electrochemical deposition process significantly improves crack-repairing performance of EDT.

Today, the world is experiencing a tremendous catastrophic disaster that can lead to potential environmental damage. However, awareness of how to deal with this catastrophic situation still remains very low. One of the most critical issues in disaster response is assigning disaster victims to the best emergency shelter location. This article reviews various existing studies to develop a new approach to determining emergency shelter locations. There are four evaluation criteria that are reviewed: optimization objective, decision variable, methodology, and victim identification. From the investigation, there are two major evaluations that can be further developed. In terms of decision variables, most of the previous research applies direct distance (Euclidean Distance) in the analysis process. However, the application of travel distance can represent a real evacuation process. Another interesting point is the victim identification process. Recent research applies grid-based partitioning and administrative-based partitioning. However, this method leads to a bias in the assignment process. This article recommends the application of K-Means clustering method as one of the unsupervised machine learning methods that is rapidly developing in many engineering fields. For better understanding, an example of K-Means clustering application is also provided in this article. Finally, the combination of travel distance and K-Means clustering will be proposed method for any further research.

Researchers are in continuous search of better strategies to minimize, if not prevent, the anthropogenic release of toxic heavy metals, such as Cu(II) and Pb(II), into drinking water resources and the natural environment. Herein, we report for the first time the low-temperature combustion synthesis of magnetic chitosan-manganese ferrite in the absence of toxic cross-linking agents and its removal of Cu(II) and Pb(II) from single-component metal solutions. The nonlinear Langmuir model best described the isotherm data, while the nonlinear pseudo-second order model best described the kinetic data, signifying monolayer Cu(II) or Pb(II) adsorption and chemisorption as the rate-determining step, respectively. Adsorption capacities by magnetic chitosan-manganese ferrite obtained for both metals were consistently higher than those by manganese ferrite, indicating that chitosan enhanced the performance of the magnetic adsorbent. The maximum adsorption capacities of magnetic chitosan-manganese ferrite for Cu(II) and Pb(II) were 14.86 and 15.36 mg g−1, while that of manganese ferrite were 2.59 and 13.52 mg g−1, respectively. Moreover, the adsorbents showed superior binding affinity and sorption for Pb(II) than Cu(II) owing to the stronger ability of the former to form inner-sphere complexes with manganese ferrite and magnetic chitosan-manganese ferrite. Finally, thermodynamic studies revealed that the uptake of either Pb(II) or Cu(II) by magnetic chitosan-manganese ferrite was spontaneous and endothermic. The as-prepared adsorbent was characterized for morphology, elemental composition, surface functional sites, and particle size using scanning electron microscopy, energy dispersive spectroscopy, Fourier transform infrared spectroscopy, and dynamic light scattering technique, respectively.

In the present work, graphene oxide (GO) was synthesized via the modified Hummers method and utilized in treating real soil washing wastewater via adsorptive removal of lead (Pb) and zinc (Zn). Characterization analysis of GO was performed using X-ray diffraction, Brunauer-Emmett-Teller method, Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, and zeta potential analysis. The Van’t Hoff, Eyring, and Arrhenius equations were applied to determine the activation and thermodynamic parameters namely activation energy (Ea), standard Gibbs energy change (ΔG°), standard enthalpy change (ΔH°), standard entropy change (ΔS°), change in activation Gibbs energy (ΔG#), change in activation enthalpy (ΔH#), and change in activation entropy (ΔS#). Based on the high coefficient of determination values (0.8882 ≥ R2 ≥ 0.9094) and low values of SSE (0.0292 ≤ SSE ≤ 0.0511) and ARE (0.8014 ≤ ARE ≤ 0.8822), equilibrium data agreed well with the Freundlich isotherm. The maximum adsorption capacity for Pb(II) and Zn(II) was determined to be 11.57 and 4.65 mg/g, respectively. Kinetic studies revealed that pseudo-second-order equation fitted well with the experimental data, which indicates that chemisorption is the rate-determining step of the adsorption system. Results have shown the possibility of GO as a potential adsorbent material in the treatment of soil washing wastewater.

This case study covers the application of the fuzzy optimization in simultaneously satisfying various constraints that include the compliance of ammonia and nitrate concentrations with stringent environmental standards. Essential components in the multi-criteria decision-making analysis is in the utilization of the Box-Behnken design (BBD) response equations, cost equations and the cumulative uncertainty of response towards the sodium chloride dosage, current density and electrolysis time parameters. The energy consumption in the electrochemical oxidation of ammonia plays an essential role in influencing the total operating cost analysis. The determination of boundary limits based on the global optimum resulted in the complete ammonia removal and USD 64.0 operating cost as its maximum boundary limits and the 40.6% ammonia removal and USD 17.1 as its minimum boundary limits. Based on the fuzzy optimal results, the overall satisfaction level incurred a decrease in adhering with a lower ammonia standard concentration (10 mg/L at 80.3% vs. 1.9 mg/L at 76.1%) due to a higher energy consumption requirement. Global optimal fuzzy results showed to be highly cost efficient (232.5% lower) as compared to using BBD alone. This demonstrates the practicality of fuzzy optimization applications in the electrochemical reactions.

The main objectives of this research are to evaluate the effects of delamination defects on the measurement of electrical resistivity of reinforced concrete slabs through analytical and experimental studies in the laboratory, and to propose a practical guide for electrical resistivity measurements on concrete with delamination defects. First, a 3D finite element model was developed to simulate the variation of electric potential field in concrete over delamination defects with various depths and lateral sizes. Second, for experimental studies, two reinforced concrete slab specimens (1500 mm (width) by 1500 mm (length) by 300 mm (thickness)) with artificial delamination defects of various dimensions and depths were fabricated. Third, the electrical resistivity of concrete over delamination defects in the numerical simulation models and the two concrete slab specimens were evaluated by using a 4-point Wenner probe in accordance with AASHTO (American Association of State Highway and Transportation Office) T-358. It was demonstrated from analytical and experimental studies in this study that shallow (50 mm depth) and deep (250 mm depth) delamination defects resulted in higher and lower electrical resistivity (ER) values, respectively, as compared to measurements performed on solid concrete locations. Furthermore, the increase in size of shallow defects resulted in an increase in concrete resistivity, whereas the increase in sizes of deep delamination defects yielded opposite results. In addition, measurements done directly above the steel reinforcements significantly lowered ER values. Lastly, it was observed from experimental studies that the effect of delamination defects on the values of electrical resistivity decreases as the saturation level of concrete increases.

A series of earthquake events give impetus to research on the ductile fracture behavior of steel materials. In the last decades, many fracture models have been developed and utilized in the mechanical or aerospace engineering. Nevertheless, very little application to structural members used in the construction industry has been made due to the lack of a suitable model for the fracture behavior of constructional steel. This paper presents the experimental and finite element (FE) technique to predict ductile fracture in mild carbon structural steel (SS275) sheets, which has been widely used in building structures. The post-necking true stress–strain responses were successfully estimated using the weighted-average method. The Bao and Wierzbicki (BW) model, which requires only two model parameters, was selected for the identification of fracture locus. Each model parameter was calibrated from uniaxial tension and in-plane shear specimens with the aid of digital image correlation (DIC) and finite element analysis. Fracture simulation was then performed and validated based on the experimental results of the specimens under combined tension and shear stress state.

In the present research, treatment of contaminated groundwater via adsorption of As(V) with an initial concentration of 50.99 &micro, g/L using chitosan-coated bentonite (CCB) was investigated. The effect of adsorbent mass (0.001 to 2.0 g), temperature (298 to 328 K), and contact time (1 to 180 min) on the removal efficiency was examined. Adsorption data was evaluated using isotherm models such as Langmuir, Freundlich, and Dubinin-Radushkevich. Isotherm study showed that the Langmuir (R2 &gt, 0.9899, &chi, 2 &le, 0.91, RMSE &le, 4.87) model best correlates with the experimental data. Kinetics studies revealed that pseudo-second order equation adequately describes the experimental data (R2 &ge, 0.9951, 0.8.33, 4.31) where equilibrium was attained after 60 min. Thermodynamics study shows that the As(V) adsorption is non-spontaneous (&Delta, G0 &ge, 0) and endothermic (&Delta, H0 = 8.31 J/mol) that would result in an increase in randomness (&Delta, S0 = 29.10 kJ/mol&bull, K) within the CCB-solution interface. FT-IR analysis reveals that hydroxyl and amino groups are involved in the adsorption of As(V) from groundwater. Results of the present research serve as a tool to determine whether CCB is an environmentally safe and cost effective material that could be utilized in a permeable reactive barrier system for the remediation of As(V) from contaminated groundwater.

In the present work, the performance of spent coffee grounds (SCG) as an adsorbent in the treatment of real soil washing wastewater (SWW) was evaluated. Scanning electron microscopy, Fourier transform infrared spectroscopy, zeta potential measurement and Brunauer–Emmett–Teller analysis were utilized to determine the physicochemical characteristics of SCG. Maximum removal efficiency of 68.73% for Cu(II), 57.23% for Pb(II) and 84.55% for Zn(II) was attained at 2.5 g SCG, 300 min and 328 K. Error analysis was performed using root mean square error (RMSE) and sum of square error (SSE). Equilibrium data correlated well with the Langmuir isotherm for Pb(II) adsorption and Freundlich model for the removal of Cu(II) and Zn(II). The kinetic study shows that adsorption of the heavy metals using SCG can be satisfactorily described using the pseudo-second order equation (R2 ≥ 0.9901; RMSE ≤ 15.0539; SSE ≤ 145.1461). Activation parameters including activation energy, change in free energy of activation, activation entropy change (ΔS*) and activation enthalpy change (ΔH*) were determined using Arrhenius and Eyring equations. Thermodynamic studies show that adsorption of the heavy metals using SCG is spontaneous, endothermic (ΔH° ≥ 9.80 kJ/mol·K) and results in increased randomness at the solid/solution interface (ΔS° ≥ 2.28 J/mol).

In this paper, the synthesis of a chitosan&ndash, montmorillonite nanocomposite material grafted with acrylic acid is presented based on its function in a case study analysis. Fuzzy optimization is used for a multi-criteria decision analysis to determine the best desirable swelling capacity (YQ) of the material synthesis at its lowest possible variable cost. For YQ, the integrating the result&rsquo, s cumulative uncertainty is an essential element to investigate the feasibility of the developed model equation. The Pareto set analysis is able to set the appropriate boundary limits for YQ and the variable cost. Two case studies are presented in determining the lowest possible cost: Case 1 for maximum YQ, and Case 2 for minimum YQ. These boundary limits were used in the fuzzy optimization to determine its global optimum results that achieved the overall satisfaction ratings of 67.2% (Case 1) and 52.3% (Case 2). The synthesis of the polyacrylic acid/chitosan material for Case 1 resulted in 305 g/g YQ and 10.8 USD/kg, while Case 2 resulted in 97 g/g YQ and 12.3 USD/kg. Thus, the fuzzy optimization approach proves to be a practical method for examining the best possible compromise solution based on the desired function to adequately synthesize a material.

The ubiquitous occurrence of heavy metals in the aquatic environment remains a serious environmental and health issue. The recovery of metals from wastes and their use for the abatement of toxic heavy metals from contaminated waters appear to be practical approaches. In this study, manganese was recovered from groundwater treatment sludge via reductive acid leaching and converted into spherical aggregates of high-purity MnO2. The as-synthesized MnO2 was used to adsorb Cu(II) and Pb(II) from single-component metal solutions. High metal uptake of 119.90 mg g−1 for Cu(II) and 177.89 mg g−1 for Pb(II) was attained at initial metal ion concentration, solution pH, and temperature of 200 mg L−1, 5.0, and 25 °C, respectively. The Langmuir isotherm model best described the equilibrium metal adsorption, indicating that a single layer of Cu(II) or Pb(II) was formed on the surface of the MnO2 adsorbent. The pseudo-second-order model adequately fit the Cu(II) and Pb(II) kinetic data confirming that chemisorption was the rate-limiting step. Thermodynamic studies revealed that Cu(II) or Pb(II) adsorption onto MnO2 was spontaneous, endothermic, and had increased randomness. Overall, the use of MnO2 prepared from groundwater treatment sludge is an effective, economical, and environmentally sustainable substitute to expensive reagents for toxic metal ion removal from water matrices.

The widespread presence of heavy metals in drinking water sources arises as a major health concern, particularly in developing countries. The development of low-cost and reliable detection techniques is identified as a societal need to provide affordable water quality control. Herein, a bismuth film-coated gold ultramicroelectrode array (BF-UMEA) was used for the detection of Pb(II) and Cd(II) in water samples via square wave anodic stripping voltammetry (SWASV). Experimental parameters such as deposition time, Bi(III) concentration, acetate buffer concentration, pH, square wave frequency, amplitude, and step potential were all varied to determine their effects on the current peak intensities of the target metal ions. Ten-fold excess in the concentration of interferences was found to cause a decrease in the stripping peak areas of Cd(II) and Pb(II) in the following order of magnitude: benzene &lt, NaCl &lt, Ni(II) &lt, Cu(II). Using Box–Behnken design, the optimum SWASV parameters that provided maximum current peak areas were 14.76 Hz (frequency), 50.10 mV (amplitude), and 8.76 mV (step potential). The limits of detection of the as-prepared BF-UMEA were 5 and 7 µg L−1 for Pb(II) and Cd(II), respectively. These results demonstrate the potential use of a BF-UMEA in SWASV for the trace quantification of Pb(II) and Cd(II) in water samples.

The primary objective of the present work is to measure the corrosion rate of reinforcing steel embedded in concrete structures in a simulated marine environment of high chloride concentration. The selection of a single frequency that corresponds to the solution resistance and single frequency that corresponds to the charge transfer resistance were performed and measurements were carried out in a relatively faster time. A total of seven cement mortar specimens were prepared. The effect of varying cover thickness (5&ndash, 50 mm) and rebar distance (10&ndash, 80 mm) on the electrical resistance of the concrete and corrosion rate of the steel was examined. To simulate the corrosion of reinforced concrete in a marine environment, cement mortars were exposed to 25 wet&ndash, dry cycles that involve an immersion for 8 h in 3 wt.% NaCl solution and drying time of 16 h under room temperature. Alternative current (AC) impedance measurements were carried out within a frequency range from 100 kHz to 1 mHz. Results show that the formation of rust layers on rebars has caused a significant decrease in the maximum phase shift to &theta, = &minus, 30&deg, An accelerated corrosion rate of the rebars was observed during drying stage.

Bathymetric mapping was traditionally implemented by shipborne single-beam, multi-beam, and side-scan sonar sensors. There are big tidal effects and the foreshore on western coastal zones of Korea. These days airborne bathymetric LiDAR technique has been attempted to get seamless geospatial data from land to submarine topography. This study focuses on generating bathymetric data near coastlines from multi-beam bathymetry and satellite altimetry gravity anomalies. The estimated bathymetry is compared with multi-beam and airborne bathymetric LiDAR data for the accuracy assessment.

In this paper we made energy consumption units of glass curtain wall type apartment and general apartment in Busan metropolitan city and compared energy consumption characteristics by building envelope. The monthly electricity consumption units of general apartment were shown in the range of which were indicated higher value in January, February, August and September with little variation. On the other hand, in case of glass curtain wall type apartment, monthly electricity consumption units were represented in the range of with significant fluctuations monthly, which were outstandingly high in July, August and September. The monthly city gas consumption units of general apartment were found to be in the range of , while glass curtain wall type apartment were within . City gas consumption units from December to March were shown highly in both type apartments. The monthly energy consumption units of general apartment were found to be within , while glass curtain wall type apartment were within . Energy consumption units of glass curtain wall type apartment were suggested 4.84 times higher than those of general apartment.

This study proposes a site location potential model for urban energy supply plants and renewable energy availability using an environment and energy geographical information system (E-GIS) database (DB) and an artificial neural network (ANN). This model addresses the technical methodology of examining the potential for the suitability of urban energy supply plants and renewable energy latency in a region for support material for urban energy supply planning in the draft plan development stage. The applicability of this model is examined by applying it for a planned city in the Republic of Korea, where urban planning is in process. The results from this study are as follows: (1) The E-GIS DB was integrated with geography, climate, and energy-related information to construct an ANN model that can manage, in an integrated manner, the factors that affect the site location of the energy supply plants. (2) The input dataset included the topography, land cover classification, accessibility, water usability, and energy demand, and the target dataset included the system capacity of domestically installed energy supply plants. (3) The site location potential model of the ANN for the urban energy supply plants and renewable energy availability was deduced, and the Levenberg–Marquardt (trainlm) and scaled conjugate gradient (trainscg) algorithms were used. The potentiality class map was constructed for 10 types of energy supply systems and renewable energy resources. (4) The applicability of this energy model was tested in the Gwang-myung/Si-heung public housing district area, a domestic ‘planned city’ of the Republic of Korea. The most appropriate urban energy supply systems for the research area were considered to be the general hydraulic power and solar power based on the topographic conditions and profitable locations for solar resources in Korea. Wind power generation was found to be the least suitable. (5) In terms of the wind energy potential, the technical wind power generation by horizontal – axis wind turbines is unattainable even in the area that has the maximum wind speed, and at least a 10-kW rated power wind turbine should be installed for vertical – axis wind turbines in the research area of interest. In terms of the solar energy potential, the maximum electric power generation potential is 413, 186 MJ/month·mesh, which is applied by mono-crystalline bulk PV.

This study proposes a new urban energy demand forecasting system that includes the following improvements: (a) a facility planning information database (DB), (b) an energy and planning statistics DB, and (c) an enhancement of the accuracy of the energy calculation method. Each of these improved aspects is involved in energy demand forecasting for urban planning. The results from this study are as follows. (1). An Environment and energy Geographical Information System Database (E-GIS DB), which provides the mesh unit facility information, was utilized to allow for the forecasting and control of urban energy demands for each unit space. (2). An energy consumption unit figure was connected with an energy simulation to diversify the level of the urban energy consumption sector and the primary energy into hourly information. This figure allows for more accurate demand forecasting. (3). Urban facilities were categorized according to energy use characteristics and were modeled to allow for energy demand forecasts. (4). The energy demand was considered in an urban climate during summer with the characteristics of the heating methods that are suitable for domestic circumstances. Thus, a separate algorithm was suggested for a cooling period and a heating/intermission period to enhance the accuracy of the demand forecasts. (5). The performance of this energy demand forecasting system was validated, such that excessively high or low calculated values can be modified from the current method in a ‘planned city’ while the urban energy demand can be forecasted relatively correct and in detail with differences of a factor of 0.20–0.44 for the cooling period in the ‘existing city’. (6). The proposed urban energy demand forecasting system was constructed as EnerISS Solver which is an automated module. This module drastically reduced time consuming for predicting energy demand and urban climate to respond for the urban energy planning subjects’ needs immediately.

This study proposes a method to create an urban planning support model, applying the Environment and energy Geographical Information System Database (E-GIS DB) through the urban life cycle to reduce energy use for environmentally friendly urban planning. The results deduced from this study are organized as follows. The proposed E-GIS construction model is composed of (a) an urban GIS integration model, (b) an E-GIS DB model, and (c) a visualization model. The urban GIS integration model has the ability to integrate urban GIS constructs as well as to connect and visualize urban planning and the environment and energy DB in 3D space. The E-GIS DB model includes a function to visualize the 2D and 3D information, which is used in the environment and energy planning of a city. To validate the proposed E-GIS construction model, a Korean city undergoing the urban planning process is selected as a case study. An E-GIS DB section with an 8 km × 12 km area for the research subject area was constructed in 2D and 3D GIS, and the urban space, climate elements, and energy distribution characteristics are compared.

The forecasted energy shortage tends to encourage to develop the next generation energy to countermove the energy problems and the climatic change all over the world. Korean government is pushing ahead with the policy for `Low Carbon Green Growth` to deal with climate changes and to overcome energy problems. And many studies for low carbon green city or zero carbon city have been progressed. In this study, energy plants and energy scenarios are selected by energy supply suited features of city at city plan. The method to evaluate energy scenario can be proposed to apply various energy plants for energy demand on city planning step and evaluation method can be systematized to be used by users. Also the calculated values are changed into index for comparison according to each energy scenario.

This paper will focus on the energy performance evaluation of a cooling plant system in a semiconductor factory. Several energy saving technologies namely: integrated cooling towers, free cooling systems, control of the chilled water quantity, etc., have been adopted to improve efficiency of the cooling plant system. We have collected actual operating data for 2 years and evaluated the performance of chillers’ COP and the whole cooling plant system's COP and they showed satisfactory results even if the thermal load of the factory was about half compared with design phase assumption. We also have verified each effect of the energy saving technologies through model-based simulation analysis. The annual electric power consumption dropped about 35% compared to conventional cooling plant systems in case of design phase thermal load. And the faulty status operation of the chiller's number control miss occurred while we monitored. Electric power consumption increased about 17% compared to normal status operation at the same period.

There are many reports about faulty status in building air-conditioning systems recently. It becomes difficult to keep indoor air temperature appropriately as faults occur, and the faults cause waste of building energy consumption. The model-based fault detection and diagnosis (FDD) methods have been researched for specific parts of air-conditioning system such as chillers, coils, variable air volume units (VAV units), etc. It needs, however, much time and labor to monitor and check every single part because we cannot predict where and when the faults occur. The purpose of this study is to examine indoor air temperature changes and energy consumption increase when faults occur and to develop an easy-to-use FDD tool that helps to find out the faulty place through the whole building air-conditioning system. And then, we treat the reliability of the proposed FDD tool and effectiveness to control of indoor environment deterioration and energy consumption increase by the tool is evaluated based on building air-conditioning system simulation in this paper.

This paper treats energy and cost performance of a cooling source system with indirect seawater utilization for air conditioning in a commercial complex. Seawater utilization has merits as a cooling source, because seawater temperature is lower than outdoor air in summer and it is cost effective because there is no water monetary cost. Actual operating data has been measured for about 2 years and the chiller and system co-efficient of performance (COP) have indicated about 4.77 and 2.93, respectively, even in summer season and the mean efficiency of the thermal storage system was about 89.9% taking into account heat loss of pumps. In addition, we have constructed simulation models for cooling tower systems, air cooling chiller systems and direct seawater utilization systems then compared them to this system. The electric power consumption of the indirect seawater utilization system was almost the same as the other systems except the air cooling chiller system, because using lower seawater temperature made the chiller efficiency higher. In conclusion, our results showed the indirect seawater utilization system was able to improve the system COP compared to air cooling chiller system, and cancel water consumption compared with the cooling tower system, and cut down an initial and maintenance costs compared with the direct seawater utilization system.

The purpose of this paper is to clarify energy performance of the cooling plant system in the industrial building using actual measured operating data and numerical simulation analysis. One aspect of industrial buildings is that they have large energy consumption for manufacturing and air-conditioning compared with office and commercial buildings. Some examples of high-efficiency technologies installed in this particular cooling plant system are inverter chillers, integrated cooling towers and a free-cooling system. The inverter chiller which has been put on the market recently is state-of-the-art technology. The maximum COP of the inverter chiller reaches about 18 under certain conditions and integrated cooling towers make lower temperature cooling water as the whole capacity is large. Actual operating data indicates satisfied values for chiller and system COP during the running period and the simulation results show that the cooling plant system can cut down annual electric power consumption by about 48% compared with conventional cooling system.