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DOE OSTI2022

Parametric Study of Panel PCM–Air Heat Exchanger Designs

Heat exchangers, devices for the transfer of heat between two or more working fluids, are extensively used in cooling applications and heating applications. Heat exchangers in buildings are typically components of space-conditioning systems, as well as of water-heating applications. Heat exchangers are also sometimes used in applications that require storage and release of energy at specific times. Phase change materials (PCMs) enhance these heat-exchange processes, given their ability to melt and solidify at a fixed range of temperatures, absorbing or releasing significant amounts of latent heat. Five different configurations of PCM–air heat exchangers for thermal control in buildings are analyzed in this work. The heat exchangers were fitted with PCM encapsulated in plastic and composite pouches of various shapes, and packaged in stackable panel layers. Three-dimensional computational fluid dynamics (CFD) modeling of coupled incompressible fluid and conjugate heat transfer were performed on the designs. The phase change process was numerically modelled using the apparent heat capacity method. Steady-state CFD simulations provided quantification of pressure drop as a function of air flow velocity. Transient simulation results describe the thermal evolution of PCM in the pouches, helping to determine the best performing configuration with respect to total thermal charging time.

10 SYNTHETIC FUELS↗

NASA NTRSDate not supplied

Hazards of Lunar Surface Exploration: Determining the Immunogenicity/Allergenicity of Lunar Dust

There are multiple Apollo program reports of lunar dust (LD) exposure leading to significant upper respiratory symptoms in select crewmembers. Possible mechanisms include particulate irritation, oxidization and release of noxious gas, or legitimate adaptive immune-mediated response. Although sterile non-protein matter would not be expected to be an allergen, one Apollo flight surgeon reported increasing symptoms upon repeated exposure, with associated eosinophilia indicative of allergy (*Acta Astronautica. 2008 63 (7–10): 980–987). Many ISS crews display a pattern of persistent immune system dysregulation and latent virus reactivation (NPJ Microgravity. 2015 Sep 3; 1:15013; NPJ Microgravity. 2017 Apr 12; 3:11). Some ISS crews manifest atypical respiratory and/or dermatitis symptoms which could have an allergic pathogenesis (J Allergy Clin. Immunol. Pract. 2016 Jul-Aug; 4(4):759-762.e8). It is logical to anticipate crew immune dysregulation would worsen during prolonged deep space missions. Planetary surface hazards will only complicate crew health risks. This study hypothesizes that LD exposure can alter susceptible individuals’ immune responses such that repeated exposure will elicit an IgE mediated allergic response either to the LD itself or concomitant antigen exposure during spaceflight. This will adversely increase clinical and operational impacts for long-duration lunar astronauts and affect countermeasure requirements for surface vehicles. Specific aims for this study are (1) Does in vitro LD exposure result in increased histamine from human peripheral blood basophils? (2) Can LD impact the capacity of CD4+ helper and/or CD19+ B-cell mediated IgE production? To address these questions, a set of in-vitro cell culture experiments will be employed (short and long term) using human peripheral blood mononuclear cells (PBMC) and basophils from both atopic and non-atopic individuals, as well as established human basophil and mast cell lines. Cells will be co-cultured with cellular mitogens, common recall antigens (tetanus, Der p1), nickel (as a possible allergenic component of LD), with or without graded amounts of LD, to study whether LD exposure for varying time intervals will alter the generation of selective immune responses associated with clinical allergic reactions. Measured outputs include supernatant-derived IgE, tryptase, histamine and selected cytokine levels. Cellular activation will be monitored by assessing activation markers via flow cytometry. EM/x-ray analysis will be used to determine cellular interactions with dust particles. The minimal amount of LD (Apollo 14 dust) and controls/simulants have been requested. This study, originally planned as an FY20/21 activity, was delayed due to the COVID pandemic. It is now scheduled to be performed during FY22.

Brian Crucian↗

NASA NTRSDate not supplied

Hazards of Lunar Surface Exploration: Determining the Immunogenicity/Allergenicity of Lunar Dust

Although infrequent, there have been Apollo program reports of lunar dust (LD) exposure leading to notable upper respiratory symptoms in select crewmembers. Possible mechanisms include particulate irritation, oxidization and release of noxious gas, or legitimate adaptive immune-mediated response. Although sterile non-protein matter would not be expected to be an allergen, one Apollo flight surgeon reported increasing symptoms upon repeated exposure with associated eosinophilia, indicative of allergy (*Acta Astronautica. 2008 63 (7–10): 980–987). Many ISS crews display a pattern of persistent immune system dysregulation and latent virus reactivation (NPJ Microgravity. 2015 Sep 3; 1:15013; NPJ Microgravity. 2017 Apr 12; 3:11). Some ISS crews manifest atypical respiratory and/or dermatitis symptoms which could have an allergic pathogenesis (J Allergy Clin. Immunol. Pract. 2016 Jul-Aug; 4(4):759-762.e8). It is logical to anticipate crew immune dysregulation would worsen during prolonged deep space missions. Planetary surface hazards will only complicate crew health risks. This study with investigate if LD exposure will elicit an IgE mediated allergic response either to the LD itself or concomitant antigen exposure during spaceflight. Allergic reactivity could adversely increase clinical and operational impacts for long-duration lunar astronauts and affect countermeasure requirements for surface vehicles. Specific aims for this study are to answer two questions: (1) Does in vitro LD exposure result in increased histamine from human peripheral blood basophils? (2) Can LD impact the capacity of CD4+ T helper and/or CD19+ B-cell mediated IgE production? To address these questions, after the proposal and selection by NASA, our laboratory has separately requested and been approved for receipt of actual LD samples from the Apollo 16 mission. These samples will be used during the study to complete the proposed set of in vitro cell culture experiments (short and long term), using human peripheral blood mononuclear cells (PBMC) and basophils from both atopic and non-atopic individuals. Cells will be co-cultured with cellular mitogens, common recall antigens (Der p1), fine ground silica quartz (as a possible allergenic component of LD), or LD, to study whether LD exposure for varying time intervals will alter the generation of selective immune responses associated with clinical allergic reactions. Measured outputs include supernatant-derived IgE, tryptase, histamine, and selected cytokine levels. Cellular activation will be monitored by assessing activation markers via flow cytometry. EM/x-ray analysis will be used to determine cellular interactions with dust particles. A series of validation experiments was initiated in FY22 once the delivery of LD was received. Based on initial experimental findings, we are optimizing the culture conditions, LD concentrations, and refining our other protocol stimuli.

Audrie A. Colorado↗

NASA NTRSDate not supplied

Hazards of Lunar Surface Exploration: Determining the Immunogenicity/Allergenicity of Lunar Dust

immunology↗

NASA NTRS2011

Immune System Dysregulation and Latent Herpesvirus Reactivation During Winterover at Concordia Station, Dome C, Antarctica

Immune system dysregulation occurs during spaceflight and consists of altered peripheral leukocyte distribution, reductions in immunocyte function and altered cytokine production profiles. Causes may include stress, confinement, isolation, and disrupted circadian rhythms. All of these factors may be replicated to some degree in terrestrial environments. NASA is currently evaluating the potential for a ground-based analog for immune dysregulation, which would have utility for mechanistic investigations and countermeasures evaluation. For ground-based space physiology research, the choice of terrestrial analog must carefully match the system of interest. Antarctica winter-over, consisting of prolonged durations in an extreme/dangerous environment, station-based habitation, isolation and disrupted circadian rhythms, is potentially a good ground-analog for spaceflight-associated immune dysregulation. Of all Antarctica bases, the French-Italian Concordia Station, may be the most appropriate to replicate spaceflight/exploration conditions. Concordia is an interior base located in harsh environmental conditions, and has been constructed to house small, international crews in a station-environment similar to what should be experienced by deep space astronauts. The ESA-NASA CHOICE study assessed innate and adaptive immunity, viral reactivation and stress factors during Concordia winterover deployment. The study was conducted over two winterover missions in 2009 and 2010. Final study data from NASA participation in these missions will be presented.

Crucian, B. E.↗

NASA NTRS2002

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

Tao, Wei-Kuo↗

NASA NTRS1999

Third and Final Shuttle Mission of the Isothermal Dendritic Growth Experiment Conducted: Highest Supercooling Ever Recorded Achieved

Dendrites describe the treelike crystal morphology commonly assumed in metals and alloys that freeze from supercooled or supersaturated melts. There remains a high level of engineering interest in dendritic solidification because the size, shape, and orientation of the dendrites determine the final microstructure of a material. It is the microstructure that then determines the physical properties of cast or welded products. Although it is well known that dendritic growth is controlled by the transport of latent heat from the moving solid-liquid interface, an accurate and predictive model has not yet been developed. The effects of gravity-induced convection on the transfer of heat from the interface have prevented adequate testing, under terrestrial conditions, of solidification models. The Isothermal Dendritic Growth Experiment (IDGE) constituted a series of three microgravity experiments flown aboard the Space Shuttle Columbia. The apparatus was used to grow and record dendrite solidification in the absence of gravity-induced convective heat transfer, thereby producing a wealth of benchmark-quality data for testing solidification models and theories.

Glicksman, Martin E.↗

NASA NTRS2012

Dynamics of Water Absorption and Evaporation During Methanol Droplet Combustion in Microgravity

The combustion of methanol droplets is profoundly influenced by the absorption and evaporation of water, generated in the gas phase as a part of the combustion products. Initially there is a water-absorption period of combustion during which the latent heat of condensation of water vapor, released into the droplet, enhances its burning rate, whereas later there is a water-evaporation period, during which the water vapor reduces the flame temperature suffciently to extinguish the flame. Recent methanol droplet-combustion experiments in ambient environments diluted with carbon dioxide, conducted in the Combustion Integrated Rack on the International Space Station (ISS), as a part of the FLEX project, provided a method to delineate the water-absorption period from the water-evaporation period using video images of flame intensity. These were obtained using an ultra-violet camera that captures the OH* radical emission at 310 nm wavelength and a color camera that captures visible flame emission. These results are compared with results of ground-based tests in the Zero Gravity Facility at the NASA Glenn Research Center which employed smaller droplets in argon-diluted environments. A simplified theoretical model developed earlier correlates the transition time at which water absorption ends and evaporation starts. The model results are shown to agree reasonably well with experiment.

Hicks, Michael C.↗

NASA NTRS2009

On Nibbles and Bytes: The Conundrum of Memory for Space Systems - NASA Electronic Parts and Packaging (NEPP) and Efforts in Memories

Radiation requirements and trends. TID: 1) >90% of NASA applications are < 100 krads-Si in piecepart requirements. a) Many commercial devices (NVM and SDRAMs) meet or come close to this. b) Charge pump TID tolerance has improved an order magnitude over the last 10 years. 2) There are always a few programs with higher level needs and, of course, defense needs SEL: 1) Prefer none or rates that are considered low risk. a) Latent damage is a bear to deal with. 2) As we re packing cells tighter and even with lower Vdd, we re seeing SEL on commercial devices regularly (<90nm). a) Often in power conversion, I/O, or control areas. SEU: 1) It s not the bit errors, it s the SEFIs errors that are the biggest issues. a) Scrubbing concerns for risk, power, speed.

LaBel, Kenneth A.↗

DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗

NASA NTRS2017

Integrated Systems Health Management for Sustainable Habitats (Using Sustainability Base as a Testbed)

Habitation systems provide a safe place for astronauts to live and work in space and on planetary surfaces. They enable crews to live and work safely in deep space, and include integrated life support systems, radiation protection, fire safety, and systems to reduce logistics and the need for resupply missions. Innovative health management technologies are needed in order to increase the safety and mission-effectiveness for future space habitats on other planets, asteroids, or lunar surfaces. For example, off-nominal or failure conditions occurring in safety-critical life support systems may need to be addressed quickly by the habitat crew without extensive technical support from Earth due to communication delays. If the crew in the habitat must manage, plan and operate much of the mission themselves, operations support must be migrated from Earth to the habitat. Enabling monitoring, tracking, and management capabilities on-board the habitat and related EVA platforms for a small crew to use will require significant automation and decision support software.Traditional caution and warning systems are typically triggered by out-of-bounds sensor values, but can be enhanced by including machine learning and data mining techniques. These methods aim to reveal latent, unknown conditions while still retaining and improving the ability to provide highly accurate alerts for known issues. A few of these techniques will briefly described, along with performance targets for known faults and failures. Specific system health management capabilities required for habitat system elements (environmental control and life support systems, etc.) may include relevant subsystems such as water recycling systems, photovoltaic systems, electrical power systems, and environmental monitoring systems. Sustainability Base, the agency's flagship LEED-platinum certified green building acts as a living laboratory for testing advanced information and sustainable technologies that provides an opportunity to test novel machine learning and controls capabilities. In this talk, key features of Sustainability Base that make it relevant to deep space habitat technology and its use of these kinds of subsystems previously listed will be presented. The fact that all such systems require less power to support human occupancy can be used as a focal point to serve as a testbed for deep space habitats that will need to operate within finite energy budgets.

Systems Health Management↗

DOE OSTI2020

On Neural Architectures for Astronomical Time-series Classification with Application to Variable Stars

Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse data sets has thus far hampered a direct intercomparison of different approaches. Here we perform the first comprehensive study of variants of NN-based learning and inference for astronomical time series, aiming to provide the community with an overview on relative performance and, hopefully, a set of best-in-class choices for practical implementations. In both supervised and self-supervised contexts, we study the effects of different time-series-compatible layer choices, namely the dilated temporal convolutional neural network (dTCNs), long-short term memory NNs, gated recurrent units and temporal convolutional NNs (tCNNs). Additionally, we also study the efficacy and performance of encoder-decoder (i.e., autoencoder) networks compared to direct classification networks, different pathways to include auxiliary (non-time-series) metadata, and different approaches to incorporate multi-passband data (i.e., multiple time series per source). Performance—applied to a sample of 17,604 variable stars (VSs) from the MAssive Compact Halo Objects (MACHO) survey across 10 imbalanced classes—is measured in training convergence time, classification accuracy, reconstruction error, and generated latent variables. We find that networks with recurrent NNs generally outperform dTCNs and, in many scenarios, yield to similar accuracy as tCNNs. In learning time and memory requirements, convolution-based layers perform better. We conclude by discussing the advantages and limitations of deep architectures for VS classification, with a particular eye toward next-generation surveys such as the Legacy Survey of Space and Time, the Roman Space Telescope, and Zwicky Transient Facility.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2004

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Hou, Arthur Y.↗

DOE OSTI2026

ZENN: A thermodynamics-inspired computational framework for heterogeneous data–driven modeling

Traditional entropy-based methods—such as cross-entropy loss in classification problems—have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence algorithms. However, the rapid growth of data across various domains has introduced new challenges, particularly the integration of heterogeneous datasets with intrinsic disparities. To address this, we introduce a zentropy-enhanced neural network (ZENN), extending zentropy theory into the data science domain via intrinsic entropy, enabling more effective learning from heterogeneous data sources. ZENN simultaneously learns both energy and intrinsic entropy components, capturing the underlying structure of multisource data. To support this, we redesign the neural network architecture to better reflect the intrinsic properties and variability inherent in diverse datasets. We demonstrate the effectiveness of ZENN on classification tasks and energy landscape reconstructions, showing its superior generalization capabilities and robustness-particularly in predicting high-order derivatives. In image and text classification tasks, ZENN demonstrates superior generalization by introducing a learnable temperature variable that models latent multisource heterogeneity, allowing it to surpass state-of-the-art models on CIFAR-10/100, BBC News, and AG News. As a practical application in materials science, we employ ZENN to reconstruct the Helmholtz energy landscape of Fe3Pt using data generated from density functional theory and capture key material behaviors, including negative thermal expansion and the critical point in the temperature–pressure space. Overall, this work presents a zentropy-grounded framework for data-driven machine learning, positioning ZENN as a versatile and robust approach for scientific problems involving complex, heterogeneous datasets.

36 MATERIALS SCIENCE↗

NASA NTRS2016

Subscale Water Based Phase Change Material Heat Exchanger Development

Supplemental heat rejection devices are required in many spacecraft as the radiators are not sized to meet the full heat rejection demand. One means of obtaining additional heat rejection is through the use of phase change material heat exchangers (PCM HX's). PCM HX's utilize phase change to store energy in unfavorable thermal environments (melting) and reject the energy in favorable environments (freezing). Traditionally, wax has been used as a PCM on spacecraft. However, water is an attractive alternative because it is capable of storing about 40% more energy per unit mass due to its higher latent heat of fusion. The significant problem in using water as a PCM is its expansion while freezing, leading to structural integrity concerns when housed in an enclosed heat exchanger volume. Significant investigation and development has taken place over the past five years to understand and overcome the problems associated with water PCM HX's. This paper reports on the final efforts by Johnson Space Center's Thermal Systems Branch to develop a water based PCM HX. The test article developed and reported on is a subscale version of the full-scale water-based PCM HX's constructed by Mezzo Technologies. The subscale unit was designed by applying prior research on freeze front propagation and previous full-scale water PCM HX development. Design modifications to the subscale unit included use of urethane bladder, decreased aspect ratio, perforated protection sheet, and use of additional mid-plates. Testing of the subscale unit was successful and 150 cycles were completed without fail.

Sheth, Rubik↗

DOE OSTI2025

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1999

Electrostatic Discharge (ESD) Failures in Thin Film Resistors

Field failures of nichrome thin film resistors have been investigated recently for several pieces of space flight hardware. These failures have involved resistance shifts ranging from a few percent to complete open circuits. Failure analysis and duplication of these failures have revealed that the failures were caused by electrostatic discharge. The failure characteristics and the circuit conditions necessary for failure have been studied for several types of thin film resistors including nichrome and tantalum nitride resistive elements. The effects of latent damage and resistive pattern design will also be discussed.

Hull, Scott M.↗

NASA NTRS1986

Heat and mass transfer in porous media phase separation at temperatures below the lambda-point of He-4

Newtonian fluid motion, coupled to heat transfer via latent heat of phase transition, is well known from numerous studies of condensation and boiling. Considerably less knowledge is available for vapor-liquid phase separation in the absence of gravity effect on the transport phenomena. The present studies are focused on heat and mass transfer associated with vapor-liquid phase separation required for long-term storage of the cryogen liquid He II in space vessels. Though space conditions are the dominant mode of interest in advanced equipment, e.g. IR telescopes, the systems may be operated in principle during terrestrial conditions. The latter are considered in the present work. It emphasizes the linear regime including an extrapolation based on variable thermophysical properties. Data taken with a phase separation approach show departures from the linear regime prediction. They agree with a transport equation proposed for the nonlinear, turbulent regime.

Yuan, S. W. K.↗