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The greenhouse gas emissions from the transportation sector are the primary cause of climate change. As a result, many studies have developed new powertrains with reduced CO2 emissions for the automotive industry. The gas turbine cycle coupled to an alternator is an autonomy booster for series hybrid electric vehicles. Many gas turbine configurations are proposed in the literature to obtain the highest cycle efficiency. This paper suggests a new architecture offering higher efficiency than all the previous cycles. The two-step methodology consists at first of a sensibility analysis using VBA and Refprop to determine the optimal operating conditions in terms of higher efficiency. The selected cycle consists of two compression stages with an intercooler, a combustion chamber, a cooled hot pressure turbine, an uncooled low-pressure turbine, and a recuperator. The efficiency of this design reaches 51.39%, which approximately matches the designs compared in the literature, but is more compact because it does not require a second combustion chamber. [ABSTRACT FROM AUTHOR]

Reversible heat pumps for electric vehicles are being developed by the car industry to address cabin heating and improve energy efficiency compared to electric heaters. For this new application, the front, louvered-fin, microchannel heat exchanger (MCHX or flat-tube heat exchanger) of the A/C system happens to operate as an evaporator under frosting conditions. MCHX are particularly sensitive to frosting, and a model is required to improve the design. This paper presents a dynamic pseudo 3D model of a fan-supplied MCHX which predicts non-uniform frost growth, air pressure losses, airflow rate and thus, thermal performances. The air pressure losses are computed considering the maximum frost thickness along each air channel. A correlation was developed to take into account frost effects on the friction factor. The model was validated against ad hoc experimental data and was also able to predict experimental data from the literature. [ABSTRACT FROM AUTHOR]

Frost growth modeling based on heat and mass diffusion through a porous media is studied in this paper. First, the basic set of equations is established. Then, the main different assumptions used to handle this basic set are presented. Thus, different models, including models found in the literature, are developed. Simulation results from the models are compared to each other and to experimental data. Impacts of each assumption are analyzed. It appears that several assumptions have dramatic impacts on the predictions. Frost thicknesses can be tripled from one model to another one. The effects of the different assumptions are explained, and recommendations to select proper assumptions are made. It appears that simple and reliable frost growth models exist. Those models are particularly suitable for applications requiring low frost growth model complexity (system modeling for instance). On the other hand, the pathway to improve predictions is also pointed out. [ABSTRACT FROM AUTHOR]

The design of efficient structures for heat and mass transfer problems involves the implementation of an appropriate topology optimization strategy in order to fully take into account the bi-objective nature of the problem. This article couples the finite-volume method (FVM), for the direct solver, with the discrete adjoint approach, for the sensitivity analysis, in order to tackle both fluid dynamic and heat transfer optimization in the frame of laminar flows. Details are provided about the sparsity pattern of the discrete adjoint system, which requires special attention to select a suitable matrix iterative solver. Several examples underline the adequacy of topology optimization in conjunction with the FVM for the minimization of the power dissipated by the fluid. Then, a bi-objective problem aiming at minimizing the pressure drop while maximizing the recoverable thermal power is solved by the identification of its Pareto frontier, thanks to an aggregate objective function (AOF) method. The main conclusion deals with the possibility of finding an acceptable trade-off between both objectives and the potential of topology optimization for heat and mass transfer optimization. [ABSTRACT FROM AUTHOR]

The solution for dynamic modeling of reheating furnaces requires a burner model, which is simultaneously accurate and fast. Based on the fact that radiative heat transfer is the most dominant heat transfer mode in high-temperature processes, the present study develops a simplified flame representation model that can be used for dynamic simulation of heat transfer in reheating furnaces. The first part of the paper investigates, experimen-tally and computationally, gas combustion in an industrial burner. Experiments aim at establishing an experimental database of the burner characteristics. This database is compared with numerical simulations in order to establish a numerical model for the burner. The numerical burner model was solved using a commercial computational fluid dynamics (CFD) software (FLUENT 6.3.26). A selection of results is presented, highlighting the usefulness of CFD as a modeling tool for industrial scale burners. In the second part of the paper, a new approach called the "emissive volume approach" is established. This approach consists of replacing the burner flame by a number of emissive volumes that replicates the radiative effect of the flame. Comparisons with CFD results show a difference smaller than 1% is achieved with the emissive volume approach, while computational time is divided by 40. [ABSTRACT FROM AUTHOR]

The multiple absorption coefficient zonal method (MACZM) is an efficient radiative heat transfer modeling method in nonisothermal inhomogeneous media. The method is of high interest for dynamic applications because of its ability to asses semitransparent radiative heat transfer in very short computation time. In this work, an efficient algorithm for MACZM is implemented. A connectivity control study is presented for taking into account the connectivity considerations required by the method. An identified ray traversal algorithm corresponding to part of the MACZM implementation is then selected among three different approaches presented in the article, based on well-known ray traver sal algorithms, the 6-tripod line algorithm and the 6-parametric line algorithm. On the other hand, the MACZM is highly parallel and is implemented in CUDA, a parallel computing architecture that enables easy use of a powerful graphics processing unit (GPU). An efficient implementation is discussed consisting of an optimal solution for exploiting the method parallelism (threading) and the use of the memory resources available on the GPU. Speed-ups going from 300 to 600 times are achieved, using a NVIDIA Tesla C 1060 GPU and an Intel Xeon CPU E5507 at 2.27 GHz. Radiative heat transfer is then simulated in a steel reheating furnace using the optimized GPU implementation. The computation time is further reduced by using a multigrid approach. [ABSTRACT FROM AUTHOR]

The efficient cooling of a finite-size volume generating heat, including adiabatic boundary conditions with the exception of a small heat sink, poses the problem of optimal allocation of high-conductivity material. Among the structural optimization methods, this article couples solid isotropic material with penalization parametrization (SIMP) with an aggregated objective function approach (AOF) to tackle this topology optimization problem through a multiobjective strategy. Both average and variance temperature-reduction problems is the solved by the identification of Pareto fronts, which are highly dependent on the quantity of the high-conductivity material. This study also underlines the link between the sensitivity analysis of both objective functions, which is required by the method of moving asymptotes (MMA). Furthermore, additional calculations have been done to include variations in heat-generation rate between two conductive materials by means of an additional penalization strategy. The main conclusion deals with the possibility of finding an acceptable trade-off between average and variance objective functions thanks to the convex shape of Pareto frontiers. [ABSTRACT FROM AUTHOR]

Abstract: Dry pressure drop in columns equipped with structured packings is considered to involve two components: drag force due to the direction changes near the column walls and in the transition region between two packing layers rotated to each other by 90°, and friction force between the different gas flows inside the crossing triangular channels and with the packing solid walls. It is believed that in a packed bed with compact sheet density and large packing surface area (above 250m2/m3), the major contribution of the pressure drop is generated by the friction component. In this paper, a model is proposed to determine the dry pressure drop friction component. The gas is assumed to establish a fully developed turbulent flow inside the structured packing channels. The structured packing geometry consists of a combination of periodic elements. It is shown that the reproduction of one periodic element aerodynamics leads to determine the gas distribution and pressure drop inside the packed bed. Therefore, modeling the dry pressure drop through one periodic element is a meaningful representation of the dry pressure drop over the packing. CFD simulations are carried out on periodic elements using different turbulence models: RNG , realizable , and SST . The best results that agree with the experimental data in the literature are obtained with the SST model. The CFD model proposed is used to study the impact of packing geometry variations on the dry pressure drop and to bring up a correlation for the pressure drop with respect to changes of packing geometry: channel height dimension, channel opening angle, and corrugation angle. [Copyright &y& Elsevier]

In this work, the multiple absorption coefficient zonal method (MACZM) is being implemented and validated numerically. The method is demonstrated to be highly suitable for the analysis of radiative heat transfer in multidimensional inhomogeneous non-grey media. A uniform rectangular fine grid is considered and small CPU time is achieved. This makes the method of great interest for transient applications. The validity of the method is demonstrated in two steps. First, cases with simple geometry are considered and results are compared to results generated by direct numerical integration. Results are also generated by MODRAY, which is a source project based on an original method called the flux-planes approximation, and are shown to be equally accurate. Second, the case of a steel reheating furnace is considered. In a previous work, the furnace heat balance and temperature profiles were simulated using a finite difference computation approach and radiative exchange factors generated by MODRAY. Experiments were performed and results generated by the model were found to be in good agreement with experimental data. The radiative exchange factors are now recalculated with MACZM. They are shown to be very close to those generated by MODRAY. The comparison of the two methods clearly shows that MACZM is much faster for the calculation of the volume-volume radiative exchange factors on a uniform rectangular grid. [ABSTRACT FROM AUTHOR]

• The coolprop thermodynamic equations of state and the implicit fitting method have been investigated for calculating the refrigerants' thermodynamic properties. • A dynamic cascade refrigeration cycle has been developed and simulated with both methods for comparison. • The simulation was 30 times faster with the implicit fitting method than coolprop equations of state. • The implicit fitting method showed high accuracy. Modeling and simulating dynamic and complex energy systems that are composed of a large number of components where every component model is described by mathematical equations can take high computational time. The calculation of the refrigerant thermodynamic properties has a big impact on the computational speed of the model. In an attempt to speed up simulations, two implementation methods for the calculation of refrigerants' thermodynamic properties were investigated, the Coolprop thermodynamic equations of state and the Implicit fitting method. A complex dynamic cascade refrigeration cycle was developed and simulated using the two fluids implementation methods. The advantages and disadvantages of each method were discussed. The results show that using the implicit fitting method instead of Coolprop for the simulations of complex dynamic systems in Dymola will accelerate the simulation by about 30 times. In addition, the implicit method is accurate and offers more flexibility for modeling complex realistic energy systems. [ABSTRACT FROM AUTHOR]

Among various topology optimization methods used in fluid flow problems, density approach has gained more interest compared to other techniques as level set approach, topological derivative technique, and phase field method. The key part of density approach is the penalized interpolation function, which forces progressively porous cells made of fluid and solid simultaneously to belong discretely to fluid or solid sub-domains. However this type of problem was only solved in mono-fluid domains, in which the method accounts for the distribution of a single fluid and a single solid. The actual work aims to extend topology optimization in fluid flow problems to bi-fluid domain. A new interpolation function was developed for this purpose. Furthermore a penalization function was integrated in the multiobjective function, which ensure that each fluid takes its own path in the device, while maintaining a minimal required solid thickness between the channels of different fluids. The results showed the capacity of the proposed method to deal with multiple fluid phases in minimizing the pressure drop while maximizing heat exchange between different flows. The main conclusion is the potential of density approach to be applied on optimization of heat exchangers. [ABSTRACT FROM AUTHOR]

Significant research efforts are considered in the automotive industry on the use of low-carbon fuels in order to reduce the emissions and improve the fuel economy of vehicles. Some of these fuels, such as the solid fuels for example, are only compatible with external combustion machines. These machines are only suitable for electrified powertrains relying on electric propulsion, in particular the extended-range-electric-vehicles with series hybrid powertrain configuration where fuel consumption strongly relies on the energy converter efficiency and power density. This paper investigates the fuel savings potential of these vehicles using a Brayton external combustion gas-turbine system as energy converter substitute to the conventional internal combustion engine. An exergo-technological explicit analysis is conducted to identify the best system configuration. A downstream-intercooled reheat external combustion gas-turbine (DIRe-ECGT) system is prioritized, offering the highest efficiency among the investigated systems. An extended-range-electric-vehicle model is developed and energy consumption simulations are performed on the worldwide-harmonized light vehicles test cycle. Fuel consumption simulation results are compared to a reference extended-range-electric-vehicle using an engine auxiliary-power-unit. Results show 6%–11.5% of fuel savings with the prioritized DIRe-ECGT auxiliary-power-unit as compared to the reference model, depending on the battery capacity and the trip distance. [ABSTRACT FROM AUTHOR]

The large-scale production of renewable energy is limited by the intermittence nature of the renewable energy sources. Moreover, the electricity production of the thermal and nuclear power plants is not flexible with the electricity demand. Hence, the integration of energy storage technologies into the grid has become crucial as it creates a balance between supply and demand for electricity and protects thereby the electrical grid. Among the large-scale energy storage technologies, a novel adiabatic compressed air energy storage (A-CAES) system will be developed in this paper. This storage system is characterized, compared to the conventional compressed air energy storage (CAES) system, by the recovery and the reuse of the compression heat in order to improve the system efficiency and avoid the use of fossil fuel sources. This paper discusses a comparison between the static and dynamic modeling of the A-CAES system performed by a computer simulation using "Modelica." Unlike the static model, the dynamic model takes into account the mechanical inertia of the turbomachinery (compressors and turbines) as well as the thermal inertia of the heat exchangers. Consequently, it enables studying the flexibility of the storage system and its ability to meet the electrical grid requirements (primary and secondary reserves) by evaluating the duration of the transient states. Furthermore, the comparison between the static and dynamic models permits to estimate the efficiency losses due to the transient evolutions.The results show that the storage system needs more than 2 min before being able to consume all the excess energy available on the electrical grid and more than 5 min before being able to produce all the energy required by the electrical grid. These time frames are due especially to the transient states (start-up) of the turbomachines. Finally, the system efficiency is 64.7%, the transient states of the system cause losses of 0.9%. These small losses are explained by the short duration of the transient states relative to that of the steady states (15 hrs). [ABSTRACT FROM AUTHOR]

This paper is devoted to the simulation of 3D transient radiation and conduction heat transfer occurring inside thin glass sheets undergoing high temperature processing. The glass is considered as an absorbing, emitting, and nonscattering medium. The zonal method is used to establish the governing radiation transfer model. Direct exchange areas are calculated by the flux planes approximation. The thin layer approximation (TLA) is then introduced for increasing CPU efficiency. Three different numerical integration schemes made possible by the TLA are presented. Comparisons are made, with calculations performed using the finite volume method (FVM). The transient coupled energy equation is solved by a full implicit control volume method using the incomplete Cholesky conjugate gradient method. The heat transfer analysis of a glass sheet residing inside a hot rectangular enclosure is studied. Results obtained by the zonal method, with or without the TLA, are in close agreement with those obtained by the FVM. CPU requirements for radiative heat transfer analysis of the zonal method with TLA are, depending on the numerical integration scheme used, between 8 and 23 times smaller than those of the zonal method without TLA. The difference between the results of the different models never exceeds 4%. The zonal method with the TLA offered significant improvements in CPU time when compared with the original zonal method with similar or acceptable accuracy. [ABSTRACT FROM AUTHOR]

The present work focuses on the application of density-based topology optimization to the design of a surface cooler. This kind of device is used to cool down the oil circuit in aircraft engines thanks to the cold air in the bypass stream, and is subject to severe heat duty and pressure drop requirements. The optimization is carried out with an in-house implementation of the density method in OpenFOAM. A continuous adjoint strategy is employed to compute the sensitivities with respect to the design variables. Avoiding the so-called “frozen turbulence” assumption, the variations of the turbulent viscosity are taken into account in the computation of the sensitivity. The proposed model also considers the influence of the design variables on the wall distance function occurring in the formulation of the Spalart–Allmaras turbulence model. A simplified two-dimensional model is first employed to tune the optimization and the density model parameters. Then, the methodology is applied to a large-scale three-dimensional case, and the results are compared to a reference straight-fin geometry. The performance is finally evaluated with a reference solver, showing that the density model overestimates both the heat exchange and the total pressure loss, but that the methodology is still able to provide efficient designs in turbulent flow, starting from a very remote initialization. [ABSTRACT FROM AUTHOR]

A methodology for parametric identification of gray-band emissivity is developed and tested on a radiant oven heating a metal sheet. Direct modeling uses the component interaction network approach that allows fast and accurate simulations. Thermal radiation modeling is done by the replating algorithm, which achieves important savings in the calculation time. The optimization is carried out with the simulated annealing algorithm. Monte Carlo simulations are used for the design of the experiment. Sensitivity analyses are done, concerning the number of temperature sensors and the measurement errors. The results show that the proposed methodology is promising. [ABSTRACT FROM AUTHOR]

Many numerical methods for computing radiation exchange in enclosures are based on the computation of direct exchange areas (DEAs) and total exchange areas (TEAs). Excessively long computation times can be associated with TEAs computation. Among the best performing methods, the plating algorithm (PA) computes TEAs from DEAs based on a set of simple recursive equations. An efficient CPU and GPU parallelization of the PA are represented. Nevertheless, PA computation complexity isO(N3). A novel formulation, the nonrecursive plating algorithm (NRPA), is introduced. It allows the computation of TEAs with a single nonrecursive step. Its equations are formulated by identification to the PA equations giving TEAs from DEAs, requiring one simple assumption. The NRPA is then written in matrix form as mainly a square matrix multiplication operation. Based on advancement in matrix multiplication computation, the NRPA complexity is proven to beO(N2.38) for the number of multiplications. CPU and GPU NRPA are implemented based on the optimized linear algebra library BLAS for CPU and cuBLAS for GPU CUDA programs. NRPA is found to highly outperform PA in both CPU and GPU computation times. Finally, a test enclosure is considered and serves to validate the accuracy of the NRPA by comparison to the PA. [ABSTRACT FROM AUTHOR]

Abstract: In this study, an exergy-based system level methodology is conducted to assess the energy penalty reduction potential of different configurations of first generation oxy-fired pulverized coal power plants. Once the process improvement potential is identified by exergy analysis on an oxy-fired plant with minimal integration, a heat integration methodology minimizing the exergy losses is carried out. Exergy analysis is employed as a guideline weighted by technological and operational constraints. This methodology has been applied to study the conventional cold flue gas recycle scheme and three alternative flue gas recirculation options including the widely studied warm recycle scheme. The integration potential of advanced cryogenic ASUs (air separation units) has also been assessed. Finally, the energy penalty associated to the capture when a high-purity CO2 flow is required has been determined. Among the different cases considered in this study, recirculation of the flue gas before the regenerative heater with an advanced ASU and a double-column CPU (compression and purification unit) leads to the highest NPE (net plant efficiency). For this case, the NPE is 39.1 % based on the lower heating value (7 %-pts energy penalty), which corresponds to a 6.5% improvement compared to the base-case plant. When high-purity CO2 is desired, the energy penalty is increased by 0.2 %-pts for the same configuration. [Copyright &y& Elsevier]

In this article, simulated annealing (SA), genetic algorithm (GA), and tabu search (TS) methods are employed separately and together for finding optimal radiant heater settings for obtaining a specific temperature profile on a design surface. Results show that all methods yield to very acceptable results for various desired temperature profiles but after different number of iterations. The GA and TS methods progress very rapidly before slowly stabilizing after a certain number of iterations, while the SA method progresses for longer periods. In addition, hybrid combinations of GA, SA, and TS proved to be better than separate ones. [ABSTRACT FROM AUTHOR]

Battery-electric buses (BEBs) are a promising technology for replacing diesel buses and reducing their environmental burden. However, their charging process can take several hours, depending on the charging technique and strategy, making them susceptible to schedule disruptions. Furthermore, the selection of the charging strategy and battery size can increase the total capital investment and operational expenses of a BEB fleet, which is a major obstacle to its adoption. Therefore, to minimize the total cost of ownership (TCO) and prevent schedule disruptions, it is essential to establish a well-defined approach to determine an appropriate battery size and charging strategy for BEB fleets. This paper presents a method for reducing the TCO of BEB by determining the optimal battery size and charging strategy for each bus while satisfying operating constraints. The method involves a two-step optimization algorithm that uses Dynamic Programming and Genetic Algorithm. The study applies this approach to the bus fleet serving line 21 in Paris and generates the optimal battery sizing, charging strategy, and required charging infrastructure. The results indicate that 100 kWh batteries offer the best trade-off between capital and operational expenditure for the fleet deployment if used with 65–85 kW chargers at bus terminals. • Proposes a co-optimization method for e-bus battery size and charging strategy • Minimizes a comprehensive cost of deployment of electric bus fleet • Considers all different types of stationary charging infrastructure • Optimizes a comprehensive list of design and operation parameters [ABSTRACT FROM AUTHOR]

Biomass conversion into biofuels and biogas is a promising way for power and heat generation. Lately, research has focused on the production of biomethane based on biomass gasification followed by methanation as an alternative to fossil natural gas. The challenge of this process remains in the intensive gas cleaning and required tar removal. In order to study tar removal from the producer gas downstream biomass gasification, solid–vapor and liquid–vapor equilibrium must be known for different tar concentrations, ranging between 0.001 and 100 g.Nm−3. To assess tar removal by condensation at low temperatures, psychrometric charts are developed. Since the composition of tar is complex, toluene, phenol, indene, naphthalene and fluoranthene are selected as tar representatives. Each component is studied separately in four different producer gas compositions formed mainly of hydrogen, carbon monoxide, carbon dioxide and methane in addition to water and nitrogen. Methods for calculating saturation, isenthalpic and constant relative concentration lines are presented. Psychrometric charts of the different tar components are finally plotted at atmospheric pressure. Results show that temperature of 196.15 K is required to reduce the tar content to 0.001 g.Nm−3. Image 1 • Tar removal via a secondary physical method at low temperature by condensation. • Fluoranthene, naphthalene, indene, phenol and toluene represent tar components. • Indicate the temperature required to start removal process per tar category. • Liquid-Vapor, Solid-Vapor equilibrium and enthalpy function of temperature. [ABSTRACT FROM AUTHOR]

In the global attempt to increase the powertrain overall efficiency of hybrid vehicles while reducing the battery size, engine waste heat recovery (WHR) systems are nowadays promising technologies. This is in particular interesting for series hybrid electric vehicles (SHEV), as the engine operates at a relative high load and under steady conditions. Therefore, the resulting high exhaust gas temperature presents the advantage of increased WHR efficiency. The Brayton cycle offers a relatively reduced weight compared to other WHR systems and presents a low complexity for integration in vehicles since it relies on an open system architecture with air as the working fluid, which consequently avoids the need for a condenser compared to the Rankine cycle. This paper investigates the potential of fuel consumption savings of a SHEV using the Brayton cycle as a WHR system from the internal combustion engine (ICE) exhaust gases. An exergy analysis is conducted on the simple Brayton cycle and several Brayton waste heat recovery (BWHR) systems were identified. A SHEV with ICE-BWHR systems is modeled, where the recovered engine waste heat is converted into electricity using an electric generator and stored in the vehicle battery. The energy consumption simulations is performed on the worldwide-harmonized light-vehicles test cycle (WLTC) while considering the additional weight of the BWHR systems. The intercooled Brayton cycle (IBC) architecture is identified as the most promising for automotive applications as it offers the most convenient compromise between high efficiency and low integration complexity. Results show that 5.5% and 7.0% improved fuel economy on plug-in and self-sustaining SHEV configurations respectively when compared to similar vehicle configurations with ICE auxiliary power units. In addition to the fuel economy improvements, the IBC-WHR system offers other intrinsic advantages such as low noise, low vibration, high durability which makes it a potential heat recovery system for integration in SHEV. [ABSTRACT FROM AUTHOR]

Standards for fuel consumption and carbon dioxide emissions are implemented worldwide in most light-duty vehicle markets. Regulatory drive cycles, defined as specific time-speed patterns, are used to measure levels of fuel consumption and emissions. These measurements should realistically reflect real world driving performance, however there is increasing concern about their adequacy due to the discrepancies observed between certified and real world consumption and emissions values. One of the main reasons for the discrepancy is that current testing protocols do not account for non-mechanical vehicle energy needs, such as passengers’ thermal comfort needs and the use of electric auxiliaries on-board. Cabin heating and cooling can especially lead to considerable increase in vehicle energy consumption. This paper presents a simulation-based assessment framework to account for the additional fuel consumption related to the cabin thermal energy and auxiliary needs under the worldwide-harmonized light vehicles test procedure (WLTP). A vehicle cabin model is developed and the thermal comfort energy needs are derived for cooling and heating, depending on ambient external temperature under cold, moderate and warm climates. A modification to the WLTP is proposed by including the generated power profiles for thermal comfort and auxiliary needs. Dynamic programming is used to compute the fuel consumption on the modified WLTP for a rechargeable series hybrid electric vehicle (SHEV) architecture. Results show consumption increases of 20% to 96% compared to the currently adopted WLTP, depending on the considered climate. [ABSTRACT FROM AUTHOR]

Partitioned approaches for the simulation of coupled conjugate heat transfer are gaining popularity in fields that require accurate thermal predictions. Considerable efforts have been put into determining stable coupling schemes, but performance enhancements have been neglected. This paper presents, for the first time, a detailed and comprehensive study of the numerical properties of Dirichlet-Robin coupling procedures, used in conjugate heat transfer simulation, with emphasis put on the optimal local coupling formulation that was recently derived from a stability analysis. This all-new optimal coupling approach provides local adaptability and has never been tested on a complex setup. This investigation looks to determine the relevance and the limitations of the theory when applied to complex conjugate heat transfer setups. The stability theory of the optimal Dirichlet-Robin coupling scheme is first recalled, then, a realistic 3D application, with complex geometry and flow structures, is used to evaluate the performance and sensitivity of Dirichlet-Robin couplings, with respect to various numerical parameters. This detailed study allows, for the first time, to evaluate the advantages and limitations of the recently proposed optimal procedure, when used on realistic 3D CHT problems. It turns out that the local optimal Dirichlet-Robin formulation outperforms all what is found in literature, and insures unconditional stability with monotone convergence for all considered setups of the 3D model. [ABSTRACT FROM AUTHOR]

• Investigation of thermo-acoustic oscillation in heavy ions superconducting linear accelerator. • Statistical study of amplitudes and frequencies of TAO. • Comparison of different TAO damping solutions. • Investigation of damping solutions side effects on cryogenic operation. SPIRAL2 is a superconducting LINAC subject to cryogenic thermoacoustic oscillations occurring in its valves boxes. 4 years of monitoring and experimental investigations with thousands of datasets turned these unwanted effects into an opportunity to study and understand thermoacoustics in a complex environment such as a real life accelerator. Without digging deep into Rott's thermoacoustics theory, thoroughly shown in other works, this paper describes the instrumentation and the methods that prepare more advanced modeling of these phenomena either to damp or to harness the energy of cryogenic thermoacoustics. [ABSTRACT FROM AUTHOR]

With the deployment of battery electric buses (BEB) increasing worldwide, proper battery sizing becomes more critical for operators as it dictates bus driving range and costs. In this paper, we present a battery sizing framework based on comprehensive energy needs assessment for BEB. The bus operating conditions are first defined for different types of bus service (City, intercity, shuttle, regional, rapid-transit). Then, BEB energy consumption is evaluated using a comprehensive energy model developed by the authors. Finally, the required battery size is estimated for different types of charging infrastructure. Modeling results show that BEB energy consumption is sensitive to bus service type, ranging widely between 2 and 4.6 kWh/km, and that intercity buses require the largest battery size (320–680 kWh). A practical finding for operators from our Paris case study is that city bus batteries are unnecessarily oversized to accommodate a typically small fraction of trips in rare extreme cold weather conditions. • Study proposes a battery sizing framework for electric buses. • Evaluates energy consumption and battery sizing for different types of bus service. • Tool to estimate the required battery size and charging infrastructures. • Bus energy consumption and battery size are sensitive to its transit service type. • City bus Batteries oversized to accommodate small number of trips during the year. [ABSTRACT FROM AUTHOR]

With the announced plans to ban diesel in major European cities from 2025, battery-powered electric buses (BEB) are attracting attention to replace diesel fleets, given their zero tailpipe emissions. However, their large-scale deployment faces several challenges, namely the limited driving range (DR) and the need for adequate charging infrastructure. The limited DR is due to the lower battery specific energy compared to oil-based fuels. Also, the use of electric auxiliaries, especially, air conditioning, reduces the DR further. The DR problem could be resolved either by increasing the battery capacity, which increases the bus cost or by rightsizing the battery alongside an adequate charging strategy to avoid schedule disruption. Therefore, this paper presents a comprehensive energy modeling of a BEB using Dymola, encompassing the different energy systems encountered in BEB. The proposed model serves as a platform to evaluate the bus energy needs during its service to properly size the battery. A powertrain model is presented to emulate the propulsion load. Then, a cabin model alongside a heating ventilating and air conditioning system are developed emulating the thermal load. Finally, auxiliaries necessary for the bus operation are modeled. The energy consumption of each system is assessed under several operating conditions. Image 1 • Study proposes a modeling methodology to assess battery electric buses energy consumption. • Assesses the impact of different driving and weather conditions and passengers load on the energy consumption. • Model serves as a platform to evaluate battery electric buses energy needs to properly size the battery. • Cabin thermal needs and auxiliaries reduce driving range by more than 50% under extreme weather and driving conditions. [ABSTRACT FROM AUTHOR]