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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives

Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit about one-third of greenhouse gases. In the last few years, machine learning has achieved a notable momentum that, if properly harnessed, may unleash its potential for advanced analytics and control of smart buildings, enabling the technique to scale up for supporting the decarbonization of the building sector. In this perspective, transfer learning aims to improve the performance of a target learner exploiting knowledge in related environments. The present work provides a comprehensive overview of transfer learning applications in smart buildings, classifying and analyzing 77 papers according to their applications, algorithms, and adopted metrics. The study identified four main application areas of transfer learning: (1) building load prediction, (2) occupancy detection and activity recognition, (3) building dynamics modeling, and (4) energy systems control. Furthermore, the review highlighted the role of deep learning in transfer learning applications that has been used in more than half of the analyzed studies. The paper also discusses how to integrate transfer learning in a smart building's ecosystem, identifying, for each application area, the research gaps and guidelines for future research directions.

Pinto, G↗
DOE OSTI2025

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗
DOE OSTI2018

Designing for Big Area Additive Manufacturing

Additive manufacturing (AM), more commonly referred to as 3D printing, is revolutionizing the manufacturing industry. With any new technology comes new rules and guidelines for the optimal use of said technology. Big Area Additive Manufacturing (BAAM), developed by Cincinnati Incorporated and Oak Ridge National Laboratory’s Manufacturing Demonstration Facility, requires a host of new design parameters compared to small-scale 3D printing to create large-scale parts. However, BAAM also creates new possibilities in material testing and various applications in the manufacturing industry. Most of the design constraints of small-scale polymer 3D printers still apply to BAAM. Beyond those constraints, new rules and limitations exist because BAAM’s large-scale system significantly changes the thermal properties associated with small-scale AM. Here, this work details both physical and software-related design considerations for additive manufacturing. After reading this guide, one will have a better understanding of slicing software’s capabilities and limitations, different physical characteristics of design and how to apply them appropriately for AM, and how to take the inherent nature of AM into consideration during the design process.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A mechanistic study on environment gas in laser powder bed fusion

A variety of protective or reactive environmental gases have recently gained growing attention in laser-based metal additive manufacturing (AM) technologies due to their unique thermophysical properties and the potential improvements they can bring to the build processes. However, much remains unclear regarding the effects of different gas environments on critical phenomena in laser AM, such as rapid cooling, energy coupling, and defect generation. Through simultaneous high-speed synchrotron x-ray imaging and thermal imaging, we identify distinct effects of two environmental gases in laser AM and gained a deeper understanding of the underlying mechanisms. Compared to the commonly used protective gas, argon, it is found that helium has a negligible effect on cooling the part. However, helium can suppress unstable keyholes by decreasing effective energy absorption, thus mitigating keyhole porosity generation and reducing pore size under certain processing conditions. In conclusion, these observations provide guidelines for the strategic use of environmental gases in laser AM to produce parts with improved quality.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Assessment of critical flaw sizes and crack driving forces during additive manufacturing of metallic materials

Additive manufacturing (AM) of complex engineering components is often plagued by a high susceptibility to cracking, particularly in high-strength metallic materials. While alloy design efforts have made progress in mitigating solidification defects, there remains a need for mechanistic guidelines to predict susceptibility to solid-state cracking. To address this gap, driving forces for the growth of melt pool cracks are calculated across a wide range of alloys using an efficient computational framework. Calculations are coupled with rapid single track laser experiments to elucidate trends in cracking from laser melting. The analyses conducted here highlight the important role of material properties in susceptibility to cracking, notably fracture toughness and elastic modulus. An important finding is that residual stresses that are limited in magnitude to the yield stress of the material are likely insufficient to drive cracking during cooling. Furthermore, the implications of these results are discussed in the context of alloy design for AM and residual stress accumulation during AM.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Assessing I 2 S-LWR economic competitiveness using systematic differential capital cost evaluation methodology

One of the major factors impeding nuclear power plant (NPP) construction is their economics. In this study, a systematic differential economics evaluation approach was developed through the use of the Code of Accounts guidelines to assess the costs of nuclear power plants. The methodology, entirely based on publicly available data, may serve as a template to evaluate direct costs for reactors of any size and design at any stage of developments. In particular, this approach was used to assess the costs of the Integral Inherently Safe Light Water Reactor (I 2 S-LWR). The I 2 S-LWR is a design concept of a large (~1000 MWe) light water reactor. One of its key design features promoting inherent safety is implementation of an integral primary circuit configuration, which however necessitates a compact design of the core and primary circuit components. Through the methodology here presented, a representative loop PWR design was taken as a reference and the differential cost was estimated for each individual account based on the design difference, or similarity. Cost scaling techniques were applied to the accounts representing systems that differ from the ones of the reference PWR. Cost estimating techniques were used to evaluate cost of innovative components that are not part of standard PWR designs. By evaluating the cost difference of the I 2 S-LWR from the standard PWR, rather than the absolute cost, the uncertainty in the estimate is reduced. A similar approach was used by ORNL to estimate the cost of a Fluoride-salt High-temperature Reactor (FHR). A traditional four-loop PWR plant with a core thermal power of 3417 MWth (1144 MWe) was selected as the reference. Costs for that plant were prepared in 1978 by the Department of Energy (DOE) Energy Economics Data Base (EEDB), averaging actual cost incurred in the construction of several nuclear power plants (NPP), itemized with a great level of detail according to the Code of Accounts. This best estimate costs are denoted PWR12-BE. For each account, the cost of equipment, site labor and site material is provided. Industry experts at Westinghouse Electric Company performed a “sanity check” of the cost items, adjusting the cost of several items to match the current market and supply chain data. The detailed cost assessment of I 2 S-LWR was performed, systematically analyzing cost for each account, and applying the differential economics approach. First, Relative importance of each account, i.e., its contribution to the total cost was established, to help focus analysis on the most significant contributors. Moreover, the accounts describing components that are different than that of the PWR12-BE were identified. The integral configuration of the reactor has important implications on the cost of the reactor plant equipment (accounts 22x). Turbine generator equipment (Accounts 23x) is not believed to be much different than that of the reference design. I 2 S-LWR structures (Accounts 21x) mainly differ from that of a standard LWR as several buildings (containment building, shield building, annex building, waste processing building, fuel storage building) are integrated into a single building (nuclear island). Yardwork has a higher cost for the I 2 S-LWR, as the NI is partially below grade. On the other hand, due to its compact Nuclear Island footprint, I 2 S-LWR facilitates (and includes in its reference version) the use of seismic isolators, which contribute to reducing the direct cost. The total capital investment cost (TCIC), on the $/kW basis, of I 2 S-LWR is 5.84% lower than that of PWR12-BE, in spite of the lower power output of I 2 S-LWR. However, for the Western US (0.7 g), benefits of the seismic isolation are more pronounced, and the I 2 S-LWR total capital investment cost is 13.02% lower than that of PWR12-BE. If the I 2 S-LWR is compared to a PWR10-BE (traditional loop design, but scaled to the same power level as I 2 S-LWR), the savings are even higher, in the range 11.12%–17.89%. The analysis indicates that I 2 S-LWR has potential to offer an economically attractive design, with TCIC lower than that of a nuclear power plant based on a traditional loop PWR design. In other words, I 2 S-LWR design offers significantly enhanced safety, while at the same time improving economics. The differential economics approach developed in this paper can be used in identifying changes in cost of key components in order to improve the economics of a nuclear reactor design. The method can also help compare the economics of advanced Generation IV reactors and innovative water-cooled SMR (Small Modular Reactors) with respect to standard LWR technologies. In summary, the differential economics approach and can be used as a tool capable of helping stakeholder decisions.

Economic↗
DOE OSTI2019

Deflection predictions of involute-shaped fuel plates using a fully-coupled numerical approach

This paper describes the modeling and simulation of fluid structure interactions (FSI) of involute-shaped fuel plates used in nuclear research reactors. We believe this to be the first time that this type of application is described in the literature using a fully-coupled, and monolithic, finite element approach. The simulations are validated against plate deflection data for the conceptual design of the Advanced Neutron Source Reactor (ANSR), which was envisioned to be the world’s most powerful nuclear research reactor for neutron scattering and other applications, but was ultimately never completed. The high performance of the ANSR creates a bounding envelope for involute-shaped research reactors such as that used in the High Flux Isotope Reactor (HFIR) at the Oak Ridge National Laboratory (ORNL) which is undergoing research for the conversion from highly-enriched uranium (HEU) to low-enriched uranium (LEU) fuel. As such, the findings from the present FSI analyses carried out herein for the ANSR plates provide good guidelines and inform designers what should be expected for the next generation of plates in the HFIR. Furthermore it is shown herein that the current approach can accurately capture the leading-edge deflections of the involute-shaped plates and simulations can predict the ‘S-shaped’ deflection of the first mode instilling confidence in the methodology.

42 ENGINEERING↗
DOE OSTI2024

A realistic TRACE PWR LOCA model with application to high-burnup analysis

This paper presents a TRACE model of a postulated large-break loss-of-coolant accident (LBLOCA) event in a four-loop pressurized water reactor (PWR). The input files have been made publicly available and serve as a starting point for researchers to improve upon or apply to their purposes. The model, based on a legacy PWR model, contains numerous improvements and modifications consistent with US Nuclear Regulatory Commission LBLOCA analysis guidelines. The model is applied to analyze high-burnup (>62 GWD/MTU) fuel behavior during LBLOCA, improving on previous work to provide realistic thermal hydraulic predictions for future fuel performance analyses and experiments related to fission fragment, relocation, and dispersal (FFRD). Sensitivity studies are presented to quantify the impact of the vessel-modeling approach, core radial discretization, and other phenomena. In conclusion, the model is intended for research purposes and contains sufficient plant geometric, operational, and safety system details to represent the main physical phenomena pertaining to LBLOCA.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Elucidating effects of catalyst loadings and porous transport layer morphologies on operation of proton exchange membrane water electrolyzers

Producing green hydrogen efficiently via proton exchange membrane water electrolysis (PEMWE) is the key for achieving decarbonization targets. Iridium catalyst is expensive, and it is important to minimize its use and to optimize interface between Ir and ionomer or water for higher utilization of catalyst in oxygen evolution reaction. In this work, x-ray computed tomography along with electrochemical and modeling techniques are used to characterize the interface for two different porous transport layers (PTLs) and catalyst layers at various loadings. We show that low porosity sintered PTLs exhibit higher interfacial contact with the catalyst and the membrane that results in improved kinetics. Radiography and modeling results indicate that oxygen taking multiple transport pathways through the PTL results in slug flow through the channels that reduces mass transport overpotential. Based on the results, we suggest design guidelines for high efficiency and durable PEMWE and their components.

08 HYDROGEN↗
DOE OSTI2016

Evaluation of “Autotune” calibration against manual calibration of building energy models

Our paper demonstrates the application of Autotune, a methodology aimed at automatically producing calibrated building energy models using measured data, in two case studies. In the first case, a building model is de-tuned by deliberately injecting faults into more than 60 parameters. This model was then calibrated using Autotune and its accuracy with respect to the original model was evaluated in terms of the industry-standard normalized mean bias error and coefficient of variation of root mean squared error metrics set forth in ASHRAE Guideline 14. In addition to whole-building energy consumption, outputs including lighting, plug load profiles, HVAC energy consumption, zone temperatures, and other variables were analyzed. In the second case, Autotune calibration is compared directly to experts’ manual calibration of an emulated-occupancy, full-size residential building with comparable calibration results in much less time. Lastly, our paper concludes with a discussion of the key strengths and weaknesses of auto-calibration approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Reactivity of novel high-performance fuels on commercial three-way catalysts for control of emissions from spark-ignition engines

The Department of Energy “Co-Optimization of Fuels and Engines” initiative aims to simultaneously develop novel high-performance fuels with advanced engine designs to reduce petroleum consumption. To achieve commercialization, advanced engines running on alternative fuels still must meet emissions regulations. Warm three-way catalysts (TWC) are very effective at meeting the stringent emissions regulations on pollutants such as nitrogen oxides (NOx), non-methane organic gases (NMOG) and carbon monoxide (CO) from gasoline-fueled spark-ignition (SI) engines operating under stoichiometric conditions; thus, most SI engine emissions occur during cold-start, when the TWC has not yet achieved light-off. In the current study, the light-off behavior of novel high-performance fuel candidates has been investigated on a hydrothermally-aged commercial TWC using a synthetic engine-exhaust flow reactor system according to industry guidelines. Over 30 potential fuel components were examined in this study, including alkanes, alkenes, alcohols, ketones, esters, aromatic ethers, and non-oxygenated aromatic hydrocarbons. Short-chain acyclic oxygenates, including alcohols, ketones, and esters, tended to light off at relatively low temperatures, while alkenes, aromatics, and cyclic oxygenates tended to light off at relatively high temperatures. The light-off behavior of alkanes and alkenes depended strongly on their size and structure. In terms of the influence on CO light-off on the TWC, the fuels fell into two distinct categories: (i) non-inhibiting species including C 2 -C 3 alcohols, alkanes, acyclic ketones, and esters; and (ii) inhibiting species including alkenes, aromatic hydrocarbons, cyclic oxygenates, and C 4 alcohols.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Nationwide HVAC Energy-Saving Potential Quantification for Office Buildings with Occupant-Centric Controls in Various Climates

The occupant-centric control (OCC) is receiving an increasing attention due to its ability to reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to investigate and quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings using a whole building simulation software EnergyPlus. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CBPM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode.

Pang, Zhihong↗
DOE OSTI2022

Application of machine learning to evaluating and remediating models for energy and environmental engineering

Machine learning (ML) algorithms have been increasingly successful in their applications to solve energy and environmental engineering problems. ML algorithms have the advantage of being able to solve highly nonlinear issues effectively. Furthermore, considering the limited sample size of data collected in energy and environmental engineering, obtaining a ML model with reasonable accuracy is simple. Unfortunately, the vast majority of the current applications of ML algorithms lack effective screening of dominant factors and comprehensive model validation, which weakens the predictive ability of the models. The present study takes the minimum miscible pressure (MMP) of CO 2 - oil systems as an example. It establishes a systematic and robust predictive model to address this issue. Based on 147 sets of slim tube tests, the predictive models of the MMPs are investigated by application of eight ML algorithms. The paper concludes that most of the published ML models in the field of energy and environmental engineering prediction are not reliable. Furthermore, it addresses the main reasons for the poor performance of some predictive models built by ML and provides guidelines on how to make such models robust. Further, to the best of our knowledge, this is the first study to point out the defects of current ML modeling methods and propose countermeasures for their application in energy and environmental engineering problems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
DOE OSTI2016

Source and distribution of naturally occurring arsenic in groundwater from Alberta’s Southern Oil Sands Regions

Arsenic (As) concentrations as high as 179 μg/L have been observed in shallow groundwater in the Alberta’s Southern Oil Sand Regions. The geology of this area of Alberta includes a thick cover (up to 200 m) of unconsolidated glacial deposits, with a number of regional interglacial sand and gravel aquifers, underlain by marine shale. Arsenic concentrations observed in 216 unconsolidated sediment samples ranged from 1 and 17 ppm. A survey of over 800 water wells sampled for As in the area found that 50% of the wells contained As concentrations exceeding drinking water guidelines of 10 μg/L. Higher As concentrations in groundwater were associated with reducing conditions. Measurements of As speciation from 175 groundwater samples indicate that As(III) was the dominant species in 74% of the wells. Speciation model calculations showed that the majority of groundwater samples were undersaturated with respect to ferrihydrite, suggesting that reductive dissolution of Fe-oxyhydroxides may be the source of some As in groundwater. Detailed mineralogical characterization of sediment samples collected from two formations revealed the presence of fresh framboidal pyrite in the deeper unoxidized sediments. Electron microprobe analysis employing wavelength dispersive spectrometry indicated that the framboidal pyrite had variable As content with an average As concentration of 530 ppm, reaching up to 1840 ppm. In contrast, the oxidized sediments did not contain framboidal pyrite, but exhibited spheroidal Fe-oxyhydroxide grains with elevated As concentrations. The habit and composition suggest that these Fe-oxyhydroxide grains in the oxidized sediment were an alteration product of former framboidal pyrite grains. X-ray absorption near edge spectroscopy (XANES) indicated that the oxidized sediments are dominated by As(V) species having spectral features similar to those of goethite or ferrihydrite with adsorbed As, suggesting that Fe-oxyhydroxides are the dominant As carriers. XANES spectra collected on unoxidized sediment samples, in contrast, indicated the presence of a reduced As species (As(-I)) characteristic of arsenopyrite and arsenian pyrite. The results of the mineralogical analyses indicate that the oxidation of framboidal pyrite during weathering may be the source of As released to shallow aquifers in this region.

58 GEOSCIENCES↗
DOE OSTI2014

An optimal guarding scheme for thermal conductivity measurement using a guarded cut-bar technique, part 1 experimental study

In the guarded cut-bar technique, a guard surrounding the measured sample and reference (meter) bars is temperature controlled to carefully regulate heat losses from the sample and reference bars. Guarding is typically carried out by matching the temperature profiles between the guard and the test stack of sample and meter bars. Problems arise in matching the profiles, especially when the thermal conductivitiesof the meter bars and of the sample differ, as is usually the case. In a previous numerical study, the applied guarding condition (guard temperature profile) was found to be an important factor in measurement accuracy. Different from the linear-matched or isothermal schemes recommended in literature, the optimal guarding condition is dependent on the system geometry and thermal conductivity ratio of sample to meter bar. To validate the numerical results, an experimental study was performed to investigate the resulting error under different guarding conditions using stainless steel 304 as both the sample and meter bars. The optimal guarding condition was further verified on a certified reference material, pyroceram 9606, and 99.95% pure iron whose thermal conductivities are much smaller and much larger, respectively, than that of the stainless steel meter bars. Additionally, measurements are performed using three different inert gases to show the effect of the insulation effective thermal conductivity on measurement error, revealing low conductivity, argon gas, gives the lowest error sensitivity when deviating from the optimal condition. The result of this study provides a general guideline for the specific measurement method and for methods requiring optimal guarding or insulation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

A review of experimental methods to determine bioaerosol transfer in energy recovery ventilators

Increasing ventilation is an effective method to reduce indoor airborne disease transmission. An Energy recovery ventilator (ERV) is a passive energy recovery device used to reduce the energy consumption of heating, ventilation and air-conditioning (HVAC) systems for conditioning the ventilation air. It preconditions the ventilation air by transferring energy from building exhaust air. Therefore, the ventilation and exhaust air streams interact directly/indirectly in the ERV for energy transfer. It is surmised that the ERV may transfer bioaerosols (with pathogens) from the exhaust air to ventilation air, resulting in the spread of infectious diseases. Consequently, many pandemic HVAC guidelines recommend that the use of ERVs be limited. This is a highly unsustainable direction given the increased energy requirements associated with the high ventilation provision advocated for pandemic operation. It must be noted that no validated experimental evidence exists in literature for bioaerosol transfer in ERVs. Hence, it is necessary to conduct extensive bioaerosol transfer research before adopting the unsustainable practice of limiting the utilization of ERVs. The main objective of this review study is to summarize the experimental methods and instrumentation for bioaerosol transfer research in ERVs. This comprehensive article provides a detailed overview of the generation, sampling, and analysis of bioaerosols for conducting the experiments. Further, it explains the possible mechanisms for bioaerosol transfer in various types of ERVs based on which the ERVs that need immediate attention are identified. The main contribution of this research paper is that it provides a novel experimental method which encompasses the biosafety aspects, instrumentation, performance parameters and uncertainties in conducting virus contained bioaerosol transfer study in ERVs. The findings from this review will be helpful in designing bioaerosol transfer experiments and developing future ERV test standards for such experiments.

42 ENGINEERING↗
DOE OSTI2026

Dynamic modeling of near isothermal compressor for Transcritical carbon dioxide cycle to support efficiency improvement

Compressors are the primary components of energy consumption in vapor compression systems, drawing considerable research effort to reduce carbon emissions and improve energy efficiency. This work presents an isothermal compressor that integrates the compression chamber with the gas cooler to achieve near-isothermal compression, resulting in up to 30% energy reduction compared to traditional isentropic compression, according to the experiment results. A detailed dynamic model for the isothermal compression cycle of carbon dioxide (CO 2 ) is first presented, coupled with a liquid-piston model for chamber design. The model is experimentally validated on a 3.5 kW prototype, yielding a 6.2% relative error in chamber pressure and a 0.5 K deviation in chamber temperature. The liquid piston exhibits reduced frictional heating and geometric adaptability relative to the mechanical piston. Leveraging these attributes, the study further evaluates approaches that enhance the heat transfer to achieve isothermal compression by increasing the effective heat transfer area during compression. As a result, simulations demonstrated up to a 5% improvement in the coefficient of performance over the baseline case through chamber design, providing guidelines for design of isothermal compression cycle.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗