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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reducing uncertainty of polar to midlatitude linkages using DOE’s E3SM in a coordinated model-experiment setting

This project brought DOE’s climate modeling effort with the Energy Exascale Earth System Model into the Polar Amplification Model Intercomparison Project (PAMIP), which is part of the sixth and latest Coupled Model Intercomparison Project, CMIP6. PAMIP examines the causes and consequences of polar amplification, when external forcing results in a larger temperature increase in high latitudes than the global average, in a coordinated set of model experiments with a common modeling protocol. Our teams from UC Irvine and the University of Toronto have designed, carried out, analyzed, and disseminated PAMIP output from the Energy Exascale Earth System Model (E3SM) and the Community Earth System Model (CESM). PAMIP’s ongoing stream of significant new results have advanced progress in the community’s understanding and led to new outstanding research questions that have motivated further work. PAMIP has led to improved consensus on the atmospheric response to sea ice loss. The important finding is that for a similar sea ice anomaly forcing, the simulated atmospheric response in the troposphere is remarkably consistent among the 16 models’ runs analyzed. The zonal-mean tropospheric response consists of a very robust equatorward shift of the westerly flow in mid-latitudes. However, while the multi-model mean response is robust, it has a weak amplitude relative to internal variability. We identified a weakness in the models (including E3SM) in terms of their response to sea-ice forcing that is related to eddy forcing (or nonlinear dynamical effects) at mid- to high latitudes. In fact, E3SM is an outlier in terms of the models participating, and in that sense, it turned out to be a vital participant model. We found that reductions in energy transport due sea-ice loss and involving dry air only are compensated by increases in moist energy transport from warmer sea surface temperature in midlatitudes. This leads to a large spread in energy transport into the Arctic and is a potential source of spread in Arctic amplification. We identified an important role that climate modes, including tropical modes of variability (El Nino and the Southern Oscillation (ENSO); the Quasi-biennial Oscillation (QBO)) play in the response to sea-ice anomalies, including in ocean coupled experiments. Similarly, we identified and quantified the contribution of sea-ice thickness to the atmospheric response compared to the response to sea-ice extent only. We found that it is important to run large ensembles and even with an ensemble size of 100 simulations the response is largely influenced by internal variability. We demonstrated convincingly that Ural blocking, not sea-ice loss, provides the weakening of the stratospheric polar vortex in fall/early winter and a negative phase of the North Atlantic Oscillation that can last for up to two months. However, sea-ice anomalies can influence the background flow so that the response to Ural blocking is more persistent under low sea-ice conditions in the Barents/Kara Sea than high sea ice Atmospheric model hierarchies that progressively add individual processes have a long history in providing dynamical insight for modeling the atmosphere. Similarly, coupled model hierarchies that progressively add individual ocean processes can provide insights into the workings of the coupled climate system, however such hierarchies have not been available except for a non-dynamical slab ocean model. Because of the missing processes, surface flux corrections must be added to produce a target climate. In this project, we managed to overcome this problem and develop a globally coupled ocean model hierarchy in CESM that can turn on and off the processes of mixed-layer entrainment and Ekman flow. We used the hierarchy to study the impact of Arctic sea-ice loss on the climate system. We find that the effect of mixed-layer entrainment on ocean heat uptake influences the atmospheric circulation by shifting the latitudinal positions of the mid-latitude westerly jet and the Intertropical Convergence Zone (ITCZ). In quadrupled CO 2 experiments, we studied how air-sea coupling affects the response of tropical rainfall under global warming. In order to identify the importance of individual ocean processes, we used the hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows, and frictional flows. We showed that including Ekman and frictional flows allows our simulation to produce the Pacific Ocean's enhanced equatorial warming pattern and equatorward ITCZ contraction noted in previous climate simulations. We also showed that the frictional flow, which has yet to receive much attention, is as important as the Ekman flow in generating equatorial heat convergence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Experiments and Simulations to Describe Alkalinity Release from Particle-Containing Oil-in-Water Emulsions and Particle Suspensions

Among the most common amendments added to groundwater during site remediation are compounds used to adjust or maintain the pH. This research describes an approach to encapsulate mineral particles (MgO and CaCO 3 ) within oil droplets suspended within an aqueous phase for the purpose of delivery to the subsurface environment. A series of batch experiments was combined with mathematical modeling to illustrate the encapsulation and understand the influence of particle encapsulation on rates and extents of alkalinity release. The encapsulation of the alkalinity-releasing particles results in slower rates of amendment release as compared to rates obtained using suspensions of bare mineral particles, allowing for the possibility of control as a function of the pH. The results indicate that the alkalinity release from particle suspensions followed a mineral dissolution mechanism that could not explain the rate of the alkalinity release of the encapsulated particles. The reduction in mineral dissolution rates observed with the encapsulated particles was found to result from a mass transfer limitation. This limitation was well described using a linear driving force expression to account for the resistance to mass transfer at the oil–water interface.

EVO↗
NASA NTRS2000

Identification of Low Order Equivalent System Models From Flight Test Data

Identification of low order equivalent system dynamic models from flight test data was studied. Inputs were pilot control deflections, and outputs were aircraft responses, so the models characterized the total aircraft response including bare airframe and flight control system. Theoretical investigations were conducted and related to results found in the literature. Low order equivalent system modeling techniques using output error and equation error parameter estimation in the frequency domain were developed and validated on simulation data. It was found that some common difficulties encountered in identifying closed loop low order equivalent system models from flight test data could be overcome using the developed techniques. Implications for data requirements and experiment design were discussed. The developed methods were demonstrated using realistic simulation cases, then applied to closed loop flight test data from the NASA F-18 High Alpha Research Vehicle.

Morelli, Eugene A.↗
NASA NTRS2001

Toward Failure Modeling In Complex Dynamic Systems: Impact of Design and Manufacturing Variations

When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes during a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the. modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle vibration monitoring systems.

Tumer, Irem Y.↗
NASA NTRS2018

GMI-IPS: Processing & Visualization Software Used in ATom DC-8 Aircraft Studies

NASA's Atmospheric Tomography Mission (ATom) deployed in each of the four seasons during 2016-2018, the DC-8 aircraft in order to establish global-scale datasets intended to improve the representation of chemically reactive gases in global atmospheric chemistry models (ACMs). The Global Modeling Initiative (GMI) executed simulations for each ATom flight using the GMI Chemistry Transport Model (GMI-CTM) to provide species concentrations of chemical gases along the DC-8 flight transects. To solve the problem of translating the GMI-CTM simulation data to the unique spatial resolutions of each ATom flight, the GMI ICARTT Processing Software (GMI-IPS) was developed.The GMI-IPS is written in Python and provides data processing, flight extraction, and visualization support for aircraft research projects using ICARTT format, which is a standard format for airborne instrument data. Additionally, the GMI-IPS interpolates global gridded model data from Hierarchical Data Format (HDF) to ICARTT compatible flight transects. Software classes for instruments and collections provided by the ATom DC-8 aircraft such as MER10, MMS, etc. are derived from a common base class. Other functionality provided by the GMI-IPS are: deriving missing flight entries along a transect, reading ICARTT entries from file, and providing Python data structures for storing flight and model information, and more.The GMI-IPS is GIT source controlled, has approximately 30,000 lines of code, and supports parallelization across data collections. It delivered GMI-CTM data for more than forty distinct DC-8 aircraft flights that took place under ATom. The output ICARTT files adhere to format standard V1.1, and pass the scan utility provided by NASA LaRC Airborne Science Data for Atmospheric Composition. This presentation will include a software and methods overview, and results from ATom, including assessments using the GMI-CTM showing how well observations from ATom flight transects represent a broader region.

Damon, M. R.↗
DOE OSTI2025

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗
NASA NTRS2017

Using A Model-Based Systems Engineering Approach For Exploration Medical System Development

NASA's Human Research Program's Exploration Medical Capabilities (ExMC) element is defining the medical system needs for exploration class missions. ExMC's Systems Engineering (SE) team will play a critical role in successful design and implementation of the medical system into exploration vehicles. The team's mission is to "Define, develop, validate, and manage the technical system design needed to implement exploration medical capabilities for Mars and test the design in a progression of proving grounds." Development of the medical system is being conducted in parallel with exploration mission architecture and vehicle design development. Successful implementation of the medical system in this environment will require a robust systems engineering approach to enable technical communication across communities to create a common mental model of the emergent engineering and medical systems. Model-Based Systems Engineering (MBSE) improves shared understanding of system needs and constraints between stakeholders and offers a common language for analysis. The ExMC SE team is using MBSE techniques to define operational needs, decompose requirements and architecture, and identify medical capabilities needed to support human exploration. Systems Modeling Language (SysML) is the specific language the SE team is utilizing, within an MBSE approach, to model the medical system functional needs, requirements, and architecture. Modeling methods are being developed through the practice of MBSE within the team, and tools are being selected to support meta-data exchange as integration points to other system models are identified. Use of MBSE is supporting the development of relationships across disciplines and NASA Centers to build trust and enable teamwork, enhance visibility of team goals, foster a culture of unbiased learning and serving, and be responsive to customer needs. The MBSE approach to medical system design offers a paradigm shift toward greater integration between vehicle and the medical system and directly supports the transition of Earth-reliant ISS operations to the Earth-independent operations envisioned for Mars. Here, we describe the methods and approach to building this integrated model.

Hanson, A.↗
DOE OSTI2023

Development of a BlueCRAB/MELCOR Framework for Supporting Realistic Mechanistic Source Term Calculations in Microreactors

Efforts are currently underway to deploy microreactor modeling and simulation tools to better support vendors and regulatory authorities in submitting and reviewing licensing applications. In particular, the Nuclear Regulatory Commission is expected to rely on the Comprehensive Reactor Analysis Bundle (BlueCRAB) multiphysics toolset in performing design- and beyond-design-basis accident analyses. In addition, the Nuclear Regulatory Commission has been using the MELCOR code to estimate mechanistic source terms during accidents. As MELCOR relies on isotopic inventory and reactor temperature/power evolution profiles during accident conditions—all of which can theoretically be obtained from BlueCRAB—the ultimate goal of this activity is to establish a common BlueCRAB-MELCOR framework. However, prior to the present research, BlueCRAB had never been used to calculate such quantities of interest at the full-core level. While there are many Monte Carlo (MC) codes capable of computing such quantities of interest, they are unable to readily account for multiphysics feedback. BlueCRAB allows for the coupling of different physics codes together to perform multiphysics-informed calculations. Therefore, the purpose of this fiscal year 2023 work is to investigate the feasibility and challenges of performing such calculations within BlueCRAB so as to generate the data that MELCOR relies on. To demonstrate the methodology, the proposed workflow was applied to a prototypical heat pipe-cooled microreactor model. To predict isotopic concentrations (taking into account the ac- cumulation of fission products during operation), the necessary microscopic cross sections were generated via OpenMC and tabulated with respect to temperature and burnup. Next, a recently developed capability in Griffin (the reactor physics application in BlueCRAB) was used to convert the OpenMC output format into the ISOXML format used by Griffin. A multiphysics microscopic depletion calculation that involved performing a coupled full-core, heterogeneous neutron trans- port and thermal calculation at each depletion step was conducted to deplete the core to end of life (EOL) conditions so as to provide both isotopics and the initial condition for the transient calculation. Following a brief null-transient to verify that the initial condition had been properly restarted and was indeed in thermal equilibrium, a heat pipe failure transient was simulated. Thus, the entire workflow of using BlueCRAB to generate MELCOR inputs, from cross-section generation to producing isotopic inventory and power/temperature evolution profiles during transients, is demonstrated. This report also details the identified gaps in the workflow and how they were (for the most part) addressed. Future work should focus on directly including MEL- COR into the workflow by performing a MELCOR calculation using the BlueCRAB-generated input data. In addition, the heat pipe reactor design should be improved so as to reflect more prototypical burnup characteristics at EOL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2005

Time Series Vegetation Aerodynamic Roughness Fields Estimated from MODIS Observations

Most land surface models used today require estimates of aerodynamic roughness length in order to characterize momentum transfer between the surface and atmosphere. The most common method of prescribing roughness is through the use of empirical look-up tables based solely on land cover class. Theoretical approaches that employ satellite-based estimates of canopy density present an attractive alternative to current look-up table approaches based on vegetation cover type that do not account for within-class variability and are oftentimes simplistic with respect to temporal variability. The current research applies Raupach s formulation of momentum aerodynamic roughness to MODIS data on a regional scale in order to estimate seasonally variable roughness and zero-plane displacement height fields using bulk land cover parameters estimated by [Jasinski, M.F., Borak, J., Crago, R., 2005. Bulk surface momentum parameters for satellite-derived vegetation fields. Agric. For. Meteorol. 133, 55-68]. Results indicate promising advances over look-up approaches with respect to characterization of vegetation roughness variability in land surface and atmospheric circulation models.

Borak, Jordan S.↗
NASA NTRS1989

Helium resonance lines in the flare of 15 June 1973

Time sequences of He I and He II resonance line intensities at several sites within the flare of June 15, 1973 are derived from observations obtained with Naval Research Laboratory's Slitless Spectroheliograph on Skylab. The data are compared with predictions in six model flare atmospheres based on two values for the heating rate and three for the flux of photoionizing coronal X-rays and EUV. A peak ionizing flux more than 1000 times that in the quiet sun is indicated. Implications for the common practice of deriving stellar coronal fluxes from He II 1640 A fluxes assuming dominance of the recombination mechanism, are discussed.

Porter, Jason G.↗
NASA NTRS2009

Synthetic and Biomass Alternate Fueling in Aviation

While transportation fueling can accommodate a broad range of alternate fuels, aviation fueling needs are specific, such as the fuel not freezing at altitude or become too viscous to flow properly or of low bulk energy density that shortens range. The fuel must also be compatible with legacy aircraft, some of which are more than 50 years old. Worldwide, the aviation industry alone uses some 85-95 billion gallons of hydrocarbon-based fossil fuel each year, which is about 10% of the transportation industry. US civil aviation alone consumes nearly 14 billion gallons. The enormity of the problem becomes overwhelming, and the aviation industry is taking alternate fueling issues very seriously. Biofuels (algae, cyanobacteria, halophytes, weeds that use wastelands, wastewater and seatwater), when properly sourced, have the capacity to be drop-in fuel replacements for petroleum fuels. As such, biojet from such sources solves the aviation CO2 emissions issue without the downsides of 'conventional' biofuels, such as competing with food and fresh water resources. Of the many current fundamental problems, the major biofuel problem is cost. Both research and development and creative engineering are required to reduce these biofuels costs. Research is also ongoing in several 'improvement' areas including refining/processing and biologics with greater disease resistance, greater bio-oil productivity, reduced water/nutrient requirements, etc. The authors' current research is aimed at aiding industry efforts in several areas. They are considering different modeling approaches, growth media and refining approaches, different biologic feedstocks, methods of sequestering carbon in the processes, fuel certification for aviation use and, overall, ensuring that biofuels are feasible from all aspects - operability, capacity, carbon cycle and financial. The authors are also providing common discussion grounds/opportunities for the various parties, disciplines and concerned organization to share both issues and potential ways for moving forward, and overall, trying to educate those concerned about the innate limitations of 'conventional' biofuels and the solutions provided by non-traditional feedstocks that used waste lands/water or saline/salt water have an immense capacity potential.

Hendricks, R. C.↗
DOE OSTI2024

Impact of Varying Dark Energy on Future Large-Scale Structure Studies

The cosmos withholds multiple mysteries such as dark forms of matter and energy that are yet beyond human comprehension. In the standard cosmological model, $\Lambda$CDM, the cosmological constant $\Lambda$ is thought to be responsible for the late accelerated expansion of the Universe. However, recent results from the Dark Energy Spectroscopic Instrument (DESI) suggest the possibility of evolving dark energy, which warrants further exploration. Future surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST) will map the large-scale structure (LSS) with unprecedented precision, giving us valuable statistical information about the cosmos. The goal of this research is to investigate the potential impact of an evolving dark energy scenario on cosmological parameters constrained by LSS probes, as will be mapped by the LSST. For this, we examine the power spectra of lens galaxies, source galaxies, and cross-power spectra between lens galaxies and source galaxies. The combination of these statistics is commonly referred to as '3 $\times$ 2 points'. For this investigation, we created a set of simulations resembling LSST data and used them to perform cosmological parameter inference in two scenarios: one in which the simulated data is based on the fiducial model and another on evolving dark energy. We then examined the degeneracy between the cosmological parameters and checked for potential shifts in the parametric space when the data contains dynamical dark energy but the modeling assumes $\Lambda$CDM. Our findings indicate that mismodeling the dark energy equation of state can significantly impact parameter inference, particularly affecting the total matter density, $\Omega_m$, and the growth of structures, as represented by the $S_8$ parameter. These results highlight the importance of further exploring extensions of the $\Lambda$CDM model in future LSS studies.

Yaman Acharya, A.↗
DOE OSTI2020

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Finally, findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1993

Intelligent systems and advanced user interfaces for design, operation, and maintenance of command management systems

Historically, command management systems (CMS) have been large and expensive spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as to develop a more generic CMS system. New technologies, in addition to a core CMS common to a range of spacecraft, may facilitate the training and enhance the efficiency of CMS operations. Current mission operations center (MOC) hardware and software include Unix workstations, the C/C++ programming languages, and an X window interface. This configuration provides the power and flexibility to support sophisticated and intelligent user interfaces that exploit state-of-the-art technologies in human-machine interaction, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of these issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, human-machine systems design and analysis tools (e.g., operator and designer models), and human-computer interaction tools (e.g., graphics, visualization, and animation) may provide significant savings in the design, operation, and maintenance of the CMS for a specific spacecraft as well as continuity for CMS design and development across spacecraft. The first six months of this research saw a broad investigation by Georgia Tech researchers into the function, design, and operation of current and planned command management systems at Goddard Space Flight Center. As the first step, the researchers attempted to understand the current and anticipated horizons of command management systems at Goddard. Preliminary results are given on CMS commonalities and causes of low re-use, and methods are proposed to facilitate increased re-use.

Potter, William J.↗
NASA NTRS1987

Predictive monitoring research: Summary of the PREMON system

Traditional approaches to monitoring are proving inadequate in the face of two important issues: the dynamic adjustment of expectations about sensor values when the behavior of the device is too complex to enumerate beforehand, and the selective but effective interpretation of sensor readings when the number of sensors becomes overwhelming. This system addresses these issues by building an explicit model of a device and applying common-sense theories of physics to model causality in the device. The resulting causal simulation of the device supports planning decisions about how to efficiently yet reliably utilize a limited number of sensors to verify correct operation of the device.

Doyle, Richard J.↗
NASA NTRS2010

Effect of High-Fidelity Ice Accretion Simulations on the Performance of a Full-Scale Airfoil Model

The simulation of ice accretion on a wing or other surface is often required for aerodynamic evaluation, particularly at small scale or low-Reynolds number. While there are commonly accepted practices for ice simulation, there are no established and validated guidelines. The purpose of this article is to report the results of an experimental study establishing a high-fidelity, full-scale, iced-airfoil aerodynamic performance database. This research was conducted as a part of a larger program with the goal of developing subscale aerodynamic simulation methods for iced airfoils. Airfoil performance testing was carried out at the ONERA F1 pressurized wind tunnel using a 72-in. (1828.8-mm) chord NACA 23012 airfoil over a Reynolds number range of 4.5x10(exp 6) to 16.0 10(exp 6) and a Mach number range of 0.10 to 0.28. The high-fidelity, ice-casting simulations had a significant impact on the aerodynamic performance. A spanwise-ridge ice shape resulted in a maximum lift coefficient of 0.56 compared to the clean value of 1.85 at Re = 15.9x10(exp 6) and M = 0.20. Two roughness and streamwise shapes yielded maximum lift values in the range of 1.09 to 1.28, which was a relatively small variation compared to the differences in the ice geometry. The stalling characteristics of the two roughness and one streamwise ice simulation maintained the abrupt leading-edge stall type of the clean NACA 23012 airfoil, despite the significant decrease in maximum lift. Changes in Reynolds and Mach number over the large range tested had little effect on the iced-airfoil performance.

Broeren, Andy P.↗
DOE OSTI2020

Modeling batch melting: Roles of heat transfer and reaction kinetics

Development of mathematical models of heat and mass transfer in glass-melting furnaces began in the 1970s and progressed rapidly with advances in sophisticated experimental/numerical techniques and increasing computational power. Today, practically all newly built or rebuilt furnaces are optimized with these models to meet stringent quality requirements, reduce the unit costs of manufacturing, or control emissions. One remaining hurdle is to model the batch-to-glass conversion accurately enough to reliably assess the glass production rate. This article summarizes two key aspects of the batch-conversion modeling—the heat transfer and the kinetics of conversion—and reviews the current state-of-the-art approaches to simulating them. We critically examine the advantages of the commonly used heat transfer approach, but also explain that its predictive capabilities are significantly restricted by the dependence of batch thermal properties on the time-temperature history. We argue that kinetic approaches to the batch-conversion modeling would offer a significant improvement when coupled with the heat transfer approach. Finally, we summarize key areas requiring further research on the way toward a realistic model of the batch blanket.

Pokorny, Richard↗
NASA NTRS1985

A procedure for space SDR prioritization

It was first necessary to arrive at a common set of attributes which described the relative importance of each Scientific Data Requirement (SDR) to the DOE CO2 Research Program. Many attributes were considered. Some were rejected because they related more to engineering considerations than to scientific ones. Finally four were selected: importance for early detection of CO2-induced effects; need for additional measurements; importance for model inputs; and importance for model outputs. Each SDR was scored on these attributes. These scores were categorical (for example, low, medium, and high) and formed the basis for assigning a relative value to each SDR. For this ranking a methodology based on dominance theory was used. The methodology and the selected SDRs are discussed.

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