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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

The 30/20 GHz fixed communications systems service demand assessment. Volume 1: Executive summary

Demand for telecommunications services is forecasted for the period 1980-2000, with particular reference to that portion of the demand associated with satellite communications. Overall demand for telecommunications is predicted to increase by a factor of five over the period studied and the satellite portion of demand will increase even more rapidly. Traffic demand is separately estimated for voice, video, and data services and is also described as a function of distance traveled and city size. The satellite component of projected demand is compared with the capacity available in the C and Ku satellite bands and it is projected that new satellite technology and the implementation of Ka band transmission will be needed in the decade of the 1990's.

Gamble, R. B.↗
NASA NTRS2012

Performance of Simple Gas Foil Thrust Bearings in Air

Foil bearings are self-acting hydrodynamics devices used to support high speed rotating machinery. The advantages that they offer to process fluid lubricated machines include: high rotational speed capability, no auxiliary lubrication system, non-contacting high speed operation, and improved damping as compared to rigid hydrodynamic bearings. NASA has had a sporadic research program in this technology for almost 6 decades. Advances in the technology and understanding of foil journal bearings have enabled several new commercial products in recent years. These products include oil-free turbochargers for both heavy trucks and automobiles, high speed electric motors, microturbines for distributed power generation, and turbojet engines. However, the foil thrust bearing has not received a complimentary level of research and therefore has become the weak link of oil-free turbomachinery. In an effort to both provide machine designers with basic performance parameters and to elucidate the underlying physics of foil thrust bearings, NASA Glenn Research Center has completed an effort to experimentally measure the performance of simple gas foil thrust bearing in air. The database includes simple bump foil supported thrust bearings with full geometry and manufacturing techniques available to the user. Test conditions consist of air at ambient pressure and temperatures up to 500 C and rotational speeds to 55,000 rpm. A complete set of axial load, frictional torque, and rotational speed is presented for two different compliant sub-structures and inter-pad gaps. Data obtained from commercially available foil thrust bearings both with and without active cooling is presented for comparison. A significant observation made possible by this data set is the speed-load capacity characteristic of foil thrust bearings. Whereas for the foil journal bearing the load capacity increases linearly with rotational speed, the foil thrust bearing operates in the hydrodynamic high speed limit. In this case, the load capacity is constant and in fact often decreases with speed if other factors such as thermal conditions and runner distortions are permitted to dominate the bearing performance.

Bruckner, Robert J.↗
DOE OSTI2021

Antitumor CD8 T cell responses in glioma patients are effectively suppressed by T follicular regulatory cells

Regulatory T (Treg) cells are thought to contribute to tumor pathogenesis by suppressing tumor immunosurveillance and antitumor immunity. T follicular regulatory (Tfr) cells are a recently characterized Treg subset that expresses both the Treg transcription factor (TF) Foxp3 and the T follicular helper (Tfh) TF Bcl-6. The role of Tfr cells in glioma patients remains unclear. In this study, we found that the level of Tfr cells, identified as Foxp3{sup +}Bcl-6{sup +} CD4 T cells, was significantly elevated in tumor-infiltrating CD4 T cells from resected glioma tumors. Both Tfr cells and Treg cells significantly suppressed the proliferation and the cytotoxic capacity of CD8 T cells toward glioma tumor cells, and the suppression was positively associated with the proportion of Tfr cells and Treg cells, respectively. Tfr and Treg cells from glioma tumor samples demonstrated higher suppression potency than those from healthy blood samples and glioma blood samples. Interestingly, canonical CXCR5{sup -} Treg cells could suppress both CXCR5{sup +} and CXCR5{sup -} CD8 T cells, albeit with stronger potency toward CXCR5{sup -} CD8 T cells. However, Tfr cells presented much higher suppression potency toward CXCR5{sup +} CD8 T cells, whereas CXCR5{sup +} CD8 T cells are a potent CD8 T cell subset previously described to have antiviral and antitumor roles. Overall, these data indicate that Tfr cells are enriched in glioma tumors and have suppressive capacity toward CD8 T cell-mediated effector functions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1980

Engineering support for magnetohydrodynamic power plant analysis and design studies

The major factors which influence the economic engineering selection of stack inlet temperatures in combined cycle MHD powerplants are identified and the range of suitable stack inlet temperatures under typical operating conditions is indicated. Engineering data and cost estimates are provided for four separately fired high temperature air heater (HTAH) system designs for HTAH system thermal capacity levels of 100, 250, 500 and 1000 MWt. An engineering survey of coal drying and pulverizing equipment for MHD powerplant application is presented as well as capital and operating cost estimates for varying degrees of coal pulverization.

Carlson, A. W.↗
NASA NTRS1981

Soil spectral characterization

The spectral characterization of soils is discussed with particular reference to the bidirectional reflectance factor as a quantitative measure of soil spectral properties, the role of soil color, soil parameters affecting soil reflectance, and field characteristics of soil reflectance. Comparisons between laboratory-measured soil spectra and Landsat MSS data have shown good agreement, especially in discriminating relative drainage conditions and organic matter levels in unvegetated soils. The capacity to measure both visible and infrared soil reflectance provides information on other soil characteristics and makes it possible to predict soil response to different management conditions. Field and laboratory soil spectral characterization helps define the extent to which intrinsic spectral information is available from soils as a consequence of their composition and field characteristics.

Stoner, E. R.↗
NASA NTRS2018

Bloom Modeling and Prediction of the Harmful Algae Alexandrium in Bellingham Bay, WA

Bellingham, Washington is located near the American-Canadian border in the northwestern part of Washington state, and is bordered on its west side by the Lummi reservation. Between Lummi and Bellingham lies Bellingham bay, which has a history of harmful algae related closures dating back to 1978. The subject of this work is a genus of dinoflagellates: Alexandrium, within which many species have the capacity to produce a suite of toxins known as saxitoxin. These toxins bioaccumulate in bivalves, which in turn cause paralytic shellfish poisoning in marine consumers (mammals, birds, and fish), including humans. Symptoms in humans can range from tingling and numbness to difficulty or inability to breathe, resulting in death. Because of the longstanding history of shellfish gathering among Salish tribes and the fact that Washington is the leading U.S. producer of farmed bivalves, harmful algae blooms impact both native and non-native peoples living in the Salish Sea area negatively. The objective of this work is to identify factors which influence Alexandrium blooms in Bellingham Bay, as well as predict Alexandrium blooms in the future. The method of doing so involves two processes: an initial statistical modeling phase to find in situ and remote sensing observations correlated to bloom density (including, but not limited to: water temperature, chlorophyll-a, salinity, color dissolved organic matter, and discharge rate of local rivers), followed by use of that data as a training set for a recursive neural network. This predictive capacity may inform future closures, help ensure the safety of shellfish consumers, and act as a baseline for future modeling efforts in the region.

Harmful↗
DOE OSTI2023

Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms

Abstract Metagenomic or metabarcoding data are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, we use an organism abundance correlation network to investigate factors that control community organization in mine tailings-derived laboratory microbial consortia grown under dozens of conditions. The network is overlaid with metagenomic information about functional capacities to generate testable hypotheses. We develop a metric to predict the importance of each node within its local network environments relative to correlated vitamin auxotrophs, and predict that a Variovorax species is a hub as an important source of thiamine. Quantification of thiamine during the growth of Variovorax in minimal media show high levels of thiamine production, up to 100 mg/L. A few of the correlated thiamine auxotrophs are predicted to produce pantothenate, which we show is required for growth of Variovorax , supporting that a subset of vitamin-dependent interactions are mutualistic. A Cryptococcus yeast produces the B-vitamin pantothenate, and co-culturing with Variovorax leads to a 90-130-fold fitness increase for both organisms. Our study demonstrates the predictive power of metagenome-informed, microbial consortia-based network analyses for identifying microbial interactions that underpin the structure and functioning of microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

A lignin-specific peroxidase in tobacco whose antisense suppression leads to vascular tissue modification

A tobacco peroxidase isoenzyme (TP60) was down-regulated in tobacco using an antisense strategy, this affording transformants with lignin reductions of up to 40-50% of wild type (control) plants. Significantly, both guaiacyl and syringyl levels decreased in essentially a linear manner with the reductions in lignin amounts, as determined by both thioacidolysis and nitrobenzene oxidative analyses. These data provisionally suggest that a feedback mechanism is operative in lignifying cells, which prevents build-up of monolignols should oxidative capacity for their subsequent metabolism be reduced. Prior to this study, the only known rate-limiting processes in the monolignol/lignin pathways involved that of Phe supply and the relative activities of cinnamate-4-hydroxylase/p-coumarate-3-hydroxylase, respectively. These transformants thus provide an additional experimental means in which to further dissect and delineate the factors involved in monolignol targeting to precise regions in the cell wall, and of subsequent lignin assembly. Interestingly, the lignin down-regulated tobacco phenotypes displayed no readily observable differences in overall growth and development profiles, although the vascular apparatus was modified.

NASA Program Fundamental Space Biology↗
DOE OSTI2021

Pore characterization of the Marcellus Shale by nitrogen adsorption and prediction of its gas storage capacity

In a shale gas reservoir, pore characterization is an important factor used to determine gas storage capacity. However, the nanometer (nm)-scale pore system in shale is difficult to explore by traditional optical, scanning electron microscopy, or even nuclear magnetic resonance well logging. We have investigated the pore structure and storage capacity of the Marcellus Shale through integration of petrophysical analysis from laboratory and well-logging data and nitrogen adsorption. The isotherm of Marcellus Shale is a composite isotherm, which has features of type I, type II, and type IV isotherms with type H4 of the hysteresis loop, suggesting slit-like pores developed in the Marcellus Shale. Quantitative analysis of pore volumes from the nitrogen adsorption indicates that density porosity may be more properly used to approximate the shale porosity and estimate the shale gas volume. In addition, the specific surface area, micropore, and mesopore volumes have a positive relationship with the kerogen volume and total organic content (TOC). By using the Langmuir and Brunauer-Emmet-Teller models, the simulated result indicates that the higher adsorbed quantity of the Marcellus Shale could be the result of the increase of micropore volume contributed, by the increase of kerogen or TOC content. The proposed equations rapidly compute TOC, a key parameter to predict gas storage capacity in overmature shale such as the Marcellus Shale.

Geochemistry & Geophysics↗
NASA NTRS2017

Models of Sector Flows Under Local, Regional and Airport Weather Constraints

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

Kulkarni, Deepak↗
NASA NTRS2017

Models of Sector Aircraft Counts in the Presence of Local, Regional and Airport Constraints

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

Kulkarni, Deepak↗
DOE OSTI2020

Drug Resistance in Filarial Parasites Does Not Affect Mosquito Vectorial Capacity

Parasite drug resistance presents a major obstacle to controlling and eliminating vector-borne diseases affecting humans and animals. While vector-borne disease dynamics are affected by factors related to parasite, vertebrate host and vector, research on drug resistance in filarial parasites has primarily focused on the parasite and vertebrate host, rather than the mosquito. However, we expect that the physiological costs associated with drug resistance would reduce the fitness of drug-resistant vs. drug-susceptible parasites in the mosquito wherein parasites are not exposed to drugs. Here we test this hypothesis using four isolates of the dog heartworm (Dirofilaria immitis)—two drug susceptible and two drug resistant—and two vectors—the yellow fever mosquito (Aedes aegypti) and the Asian tiger mosquito (Ae. albopictus)—as our model system. Our data indicated that while vector species had a significant effect on vectorial capacity, there was no significant difference in the vectorial capacity of mosquitoes infected with drug-resistant vs. drug-susceptible parasites. Consequently, contrary to expectations, our data indicate that drug resistance in D. immitis does not appear to reduce the transmission efficiency of these parasites, and thus the spread of drug-resistant parasites in the vertebrate population is unlikely to be mitigated by reduced fitness in the mosquito vector.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Utility-Scale Solar, 2023 Edition: Empirical Trends in Deployment, Technology, Cost, Performance, PPA Pricing, and Value in the United States [Slides]

Berkeley Lab’s “Utility-Scale Solar, 2023 Edition” presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC (PV plants of 5 MWAC or less, including residential rooftop systems, are covered separately in Berkeley Lab’s companion annual report, Tracking the Sun). Highlights of this year’s update include: -10.4 GWAC of new utility-scale PV capacity came online in 2022, bringing cumulative installed capacity to more than 61.7 GWAC across 46 states. -94% of all new utility-scale PV capacity added in 2022 uses single-axis tracking. -Median installed project costs declined to $\$1.32$/WAC (or $\$1.07$/WDC) in 2022. -Plant-level capacity factors vary widely, from 9% to 35% (on an AC basis), with a sample median of 24%. The report explores drivers of this variation. -Utility-scale PV’s LCOE fell to $\$39$/MWh in 2022 ($\$29$/MWh if factoring in the federal investment tax credit, or ITC). -PPA prices have largely followed the decline in solar’s LCOE over time, but have recently stagnated and even moved slightly higher. Prices from a sample of recent contracts average around $\$20-30$/MWh (levelized) in the West and $\$30-40$/MWh elsewhere in the continental US. -In 2022, solar’s average market value (defined in the report to include only energy and capacity value) rose by 40% to $\$71$/MWh and exceeded average wholesale prices in 4 of the 7 ISOs/RTOs and 11 of 18 other balancing authorities analyzed. -Adding battery storage is one way to increase the value of solar. Our public data file tracks metadata and PPA prices from ~100 PV+battery hybrid projects that are already online or that have secured offtake arrangements. -the end of 2022, there were at least 947 GW of utility-scale solar power capacity within the interconnection queues across the nation, 456 GW of which include batteries. For more information, and to explore related interactive data visualizations, go to utilityscalesolar.lbl.gov.

14 SOLAR ENERGY↗
NASA NTRS1996

Queuing Models of Tertiary Storage

Large scale scientific projects generate and use large amounts of data. For example, the NASA Earth Observation System Data and Information System (EOSDIS) project is expected to archive one petabyte per year of raw satellite data. This data is made automatically available for processing into higher level data products and for dissemination to the scientific community. Such large volumes of data can only be stored in robotic storage libraries (RSL's) for near-line access. A characteristic of RSL's is the use of a robot arm that transfers media between a storage rack and the read/write drives, thus multiplying the capacity of the system. The performance of the RSL's can be a critical limiting factor for the performance of the archive system. However, the many interacting components of an RSL make a performance analysis difficult. In addition, different RSL components can have widely varying performance characteristics. This paper describes our work to develop performance models of an RSL in isolation. Next we show how the RSL model can be incorporated into a queuing network model. We use the models to make some example performance studies of archive systems. The models described in this paper, developed for the NASA EODIS project, are implemented in C with a well defined interface. The source code, accompanying documentation, and also sample JAVA applets are available at: http://www.cis.ufl.edu/~ted/

Johnson, Theodore↗
NASA NTRS2003

Frequency Reuse, Cell Separation, and Capacity Analysis of VHF Digital Link Mode 3 TDMA

The most recent studies by the Federal Aviation Administration (FAA) and the aviation industry have indicated that it has become increasingly difficult to make new VHF frequency or channel assignments to meet the aviation needs for air-ground communications. FAA has planned for several aggressive improvement measures to the existing systems, but these measures would not meet the projected voice communications needs beyond 2009. FAA found that since 1974 there has been, on the average, a 4 percent annual increase in the number of channel assignments needed to satisfy the air-ground communication traffic (approximately 300 new channel assignments per year). With the planned improvement measures, the channel assignments are expected to reach a maximum number of 16615 channels by about 2010. Hence, the FAA proposed the use of VDL Mode 3 as a new integrated digital voice and data communications systems to meet the future air traffic demand. This paper presents analytical results of frequency reuse; cell separation and capacity estimation of VDL Mode 3 TDMA systems that FAA has planned to implement the future VHF air-ground communications system by the year 2010. For TDMA, it is well understood that the frequency reuse factor is a crucial parameter for capacity estimation. Formulation of this frequency reuse factor is shown, taking into account the limitation imposed by the requirement to have a sufficient Signal to Co-Channel Interference Ratio. Several different values for the Signal to Co-Channel Interference Ratio were utilized corresponding to the current analog VHF DSB-AM systems, and the future digital VDL Mode 3. The required separation of Co-Channel cells is computed for most of the Frequency Protected Service Volumes (FPSV's) currently in use by the FAA. Additionally, the ideal cell capacity for each FPSV is presented. Also, using actual traffic for the Detroit air space, a FPSV traffic distribution model is used to generate a typical cell for channel capacity prediction. Such prediction is useful for evaluating the improvement of future VDL Mode 3 deployment and capacity planning.

Shamma, Mohammed A.↗
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Renewable Energy Potential Model: Hawaii Geothermal Supply Curves

This dataset extends the development of the Renewable Energy Potential (reV) model to include geothermal energy, with a specific focus on Hawaii. Provided here are the results of two scenarios that were modeled for geothermal energy in Hawaii: binary enhanced geothermal systems (EGS) at a depth of 2.5 km and hydrothermal binary systems at a depth of 1.5 km. The resource data for both scenarios were derived from Lautze and Haskins (2024) using an exponential method. The PFA probability of heat map was used as a look up table for which temperature gradient to use (Lautze and Haskins, 2024). The dataset provides geospatial and techno-economic details for evaluating geothermal energy potential. It includes spatial coordinates, estimated capacity factors, developable area, resource potential, and annual energy production metrics. Economic details such as levelized cost of electricity (LCOE), site development costs, transmission costs, and fixed-charge rates are also included. The reV model, originally developed for wind and solar energy, incorporates these variables to evaluate deployment constraints related to land use, environmental and cultural factors, and grid integration.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

The role of moisture in MgCl 2 salt: A multiscale approach to TES performance

This study presents a comprehensive multiscale analysis to evaluate the influence of moisture on the thermal performance of thermal energy storage systems using magnesium chloride (MgCl 2 ) as the phase-changing material. The system uses graphite foam with 90% relative density to enhance thermal conductivity. The analysis includes thermal conductivity calculations and specific heat capacity for different hydrate phases of MgCl 2 : Anhydrous, Mono, Di, Tetra, and Hexa. These properties were evaluated for the first time using the phonon density of states from Density Functional Theory simulations. Results showed that thermal conductivity decreased, while specific heat capacity increased by a factor of two as the phase changed from anhydrous to hexahydrate. Meso-scale models were created to account for the anisotropy of graphite foam and property variations of the MgCl 2 hydrate phases. Asymptotic Expansion homogenization simulations determined the anisotropic thermal conductivity for all phases. This unique methodology improved simulation accuracy, which matched experimental data for anhydrous MgCl 2 . A parametric study examined various operating conditions and their effect on TES performance. It revealed that higher charging temperatures did not enhance exergy efficiency, but increased discharge mass flow rates improved it due to better heat transfer. Thermal performance evaluated by the exergy efficiency remained consistent across hydrate systems under the tested conditions. Furthermore, the study suggests that this uniformity is linked to missing key data, particularly latent heat and melting point for different hydrates. Overall, it highlights the importance of multiscale effects and accurate material properties in designing and optimizing TES systems.

Molten salt degradation↗