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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
NASA NTRS1995

USML-1 Glovebox experiments

This report covers the development of and results from three experiments that were flown in the Materials Science Glovebox on USML-1: Marangoni convection in Closed Containers (MCCC), Double Float Zone (DFZ), and Fiber Pulling in Microgravity (FPM). The Glovebox provided a convenient, low cost method for doing simple 'try and see' experiments that could test new concepts or elucidate microgravity phenomena. Since the Glovebox provided essentially one (or possibly two levels of confinement, many of the stringent verification and test requirements on the experiment apparatus could be relaxed and a streamlined test and verification plan for flight qualification could be implemented. Furthermore, the experiments were contained in their own carrying cases whose external configurations could be identified early in the integration sequence for stowage considerations while delivery of the actual experiment apparatus could be postponed until only a few months before flight. This minimized the time fluids must be contained and reduced the possibility of corrosive reactions that could ruin the experiment. In many respects, this exercise was as much about developing a simpler, cheaper way of doing crew-assisted science as it was about the actual scientific accomplishments of the individual experiments. The Marangoni Convection in Closed Containers experiment was designed to study the effects of a void space in a simulated Bridgman crystal growth configuration and to determine if surface tension driven convective flows that may result from thermal gradients along any free surfaces could affect the solidification process. The Fiber Pulling in Microgravity experiment sought to separate the role of gravity drainage from capillarity effects in the break-up of slender cylindrical liquid columns. The Stability of a Double Float Zone experiment explored the feasibility of a quasi-containerless process in which a solidifying material is suspended by two liquid bridges of its own melt.

Naumann, Robert J.↗
NASA NTRS1995

Flight demonstration of flight termination system and solid rocket motor ignition using semiconductor laser initiated ordnance

Solid State Laser Initiated Ordnance (LIO) offers new technology having potential for enhanced safety, reduced costs, and improved operational efficiency. Concerns over the absence of programmatic applications of the technology, which has prevented acceptance by flight programs, should be abated since LIO has now been operationally implemented by the Laser Initiated Ordnance Sounding Rocket Demonstration (LOSRD) Program. The first launch of solid state laser diode LIO at the NASA Wallops Flight Facility (WFF) occurred on March 15, 1995 with all mission objectives accomplished. This project, Phase 3 of a series of three NASA Headquarters LIO demonstration initiatives, accomplished its objective by the flight of a dedicated, all-LIO sounding rocket mission using a two-stage Nike-Orion launch vehicle. LIO flight hardware, made by The Ensign-Bickford Company under NASA's first Cooperative Agreement with Profit Making Organizations, safely initiated three demanding pyrotechnic sequence events, namely, solid rocket motor ignition from the ground and in flight, and flight termination, i.e., as a Flight Termination System (FTS). A flight LIO system was designed, built, tested, and flown to support the objectives of quickly and inexpensively putting LIO through ground and flight operational paces. The hardware was fully qualified for this mission, including component testing as well as a full-scale system test. The launch accomplished all mission objectives in less than 11 months from proposal receipt. This paper concentrates on accomplishments of the ordnance aspects of the program and on the program's implementation and results. While this program does not generically qualify LIO for all applications, it demonstrated the safety, technical, and operational feasibility of those two most demanding applications, using an all solid state safe and arm system in critical flight applications.

Schulze, Norman R.↗
NASA NTRS1999

Design of the Automated Rendezvous and Capture Docking System

This paper describes the Automated Rendezvous and Capture (AR&C) system that was designed and is being tested at NASA's Marshall Space Flight Center (MSFC). The AR&C system incorporates some of the latest innovations in Global Positioning System (GPS), laser sensor technologies and automated mission sequencing algorithms as well as the capability for ground and crew monitoring and commanding. This paper summarizes the variety of mission scenarios supported by the AR&C system. It also describes the major components of the AR&C system including the Guidance, Navigation and Control system, GPS receivers, relative navigation filter and the Video Guidance Sensor. A discussion of the safety and reliability issues confronted during the design follows. By designing a safe and robust automated system, space mission operations cost can be reduced by decreasing the number of ground personnel required for the extensive mission design, preflight planning and training typically required for rendezvous and docking missions.

Cruzen, Craig A.↗
NASA NTRS2000

Microgravity Disturbance Characterization of the Quench Module Insert (QMI) Phase Change Device (PCD)

The Materials Science Research Facility (MSRF) is a multi-user, multi-purpose facility for materials science research. One experiment within the MSRF will be the Quench Module Insert (QMI), a high-temperature furnace with unique capabilities for processing different classes of materials. The primary functions of the QMI furnace are to melt, directionally solidify, and quench metallic samples, providing data to aid in understanding the effects of the microgravity environment on the characteristics of these processed metals. The QMI houses sealed individual sample ampoules containing material to be processed. Quenching of the samples in the QMI furnace is accomplished by releasing low-melting-point metallic shoes into contact with the outside of the sample ampoule, dissipating heat and cooling the sample inside. The impact from this method of quench will induce sample vibrations which could be large enough to adversely affect sample quality. Utilizing breadboard hardware, the sample quench sequence, releasing the shoes, was conducted. Data was collected from accelerometers located on the breadboard sample cartridge, indicating the maximum acceleration achieved by the sample. The primary objective of the test described in this presentation was to determine the acceleration imparted on the sample by the shoe contact. From this information, the science community can better assess whether this method of quench will allow them to obtain the data they need.

Gattis, Christy↗
NASA NTRSDate not supplied

Method Development for Multiplex, In-Situ, and Real-Time Detection of Herpesvirus Reactivation in Spaceflight Crews using Nanopore Sequencing

Reactivation of latent herpesviruses in crews onboard the International Space Station (ISS) is a well-established spaceflight-associated phenomenon and has been linked to overall immune stress. Beyond an indicator of an altered immune state, this stress-induced reactivation of viruses such as herpesvirus simplex virus 1 (HSV-1), Epstein-Barr virus (EBV), and Varicella-Zoster virus (VZV) may cause clinical symptoms in crew. There is currently no established protocol for in-flight monitoring, and samples are analyzed post-flight using ground-based assays. A real-time, in-flight method for herpesvirus detection followed by stress-mitigation strategies would be a significant advance. In this study, we developed a real-time assay for the multiplex detection of HSV-1, EBV, and VZV from saliva that could be implemented for in-situ monitoring of ISS crew. This method builds on previously validated spaceflight-compatible portable molecular protocols and platforms, such as the miniPCR thermal cycler and the MinION sequencer. Since a metagenomic approach is not currently permitted for crew samples (NASA policy), we employed multiplexing-ready primers directed toward targeted regions within the HSV-1, EBV, and VZV genomes. We also used primers for the human gene, Statherin (STATH), as an internal control. These primers were validated using spiked-in, positive control HSV-1, EBV, and VZV from virus-negative saliva extracted using the Zymo-Research Quick-DNA/RNA Viral MagBead Kit. The PCR Barcoding Kit was used to prepare DNA libraries that were then sequenced on the MK1C and analyzed against known reference genomes using minimap2. Following validation of this method with spiked saliva samples, suspected herpesvirus-positive clinical saliva samples were successfully tested. Prior to use onboard the ISS, this method will be deployed to an analog environment during overwintering at Palmer Station, Antarctica in 2023. This work represents the successful application of molecular technologies currently onboard the ISS for the real-time monitoring of latent herpesvirus reactivation from saliva samples. This assay, in combination with stress-reduction strategies, holds the potential to manage herpesvirus reactivation in ISS crew, thereby improving health outcomes and overall immunity.

Patrick M. Rydzak↗
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets

Abstract Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

Vik, Dean (ORCID:000000027546899X)↗
NASA NTRS1983

LaNi5 hydride cryogenic refrigerator test results

A complete LaNi5 hydrogen absorption cryogenic refrigerator system was developed. The system uses low temperature waste heat of approximately 100 C as a power source, and has no moving parts other than self operating valves. The cycle continues automatically by an electronic sequencing timing mechanism for the three compressors which are phased such that a constant supply of high pressure hydrogen gas is provided. It is indicated that with a fully clean hydrogen system, hundreds of thousand cycles should be attainable, even though some degradation may eventually occur. Simple vacuum reactivation of the hydride of moving parts, other than self operating, long life valves, the refrigerators predicted life is extremely long.

Jones, J. A.↗
DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗
DOE OSTI2021

A generic method for interfacing IEDs using low voltage interfaces to real-time simulators with hardware in the loop

This study presents an interface method (IM) to interconnect real-time simulators (RTSs) without amplifiers for different intelligent electronic devices (IEDs), such as protective relays, smart meters, and other devices. It is a significant topic for the power systems protection community because there are many protection devices with different requirements. These protection devices have pinouts that measure bus voltages/currents and breaker pole states and generate trip/close pulse signals. Most of the emulation test beds with RTSs and HIL need amplifiers to connect IEDs from different product manufacturers because the low-voltage interface levels are not available in some instruction manuals. Additionally, commercial amplifiers have cutoff frequency limitations and have an excessive cost when several IEDs are wired onto test beds. Then, the validation of protection and control systems with RTSs and IEDs in the loop from different vendors without amplifiers results in an unfeasible alternative. In this paper, the IM was based on using an interface box, power source, and RTS to identify IED inputs/outputs. Here, the sequence to recognize IED pinouts and calculate the current/voltage scaling factors is described. The IM was validated satisfactorily with RTS and a protection device (with unknown pinouts) in the loop.

42 ENGINEERING↗
DOE OSTI2021

Novel compound heterozygous CPLANE1 variants identified in a Chinese family with Joubert syndrome

Abstract Joubert syndrome (JS) and JS‐related disorders (JSRD) are a group of neurodevelopmental diseases that share the “molar tooth sign” on axial brain magnetic resonance imaging (MRI), accompanied by cerebellar vermis hypoplasia, ataxia, hypotonia, and developmental delay. To identify variants responsible for the clinical symptoms of a Chinese family with JS and to explore the genotype–phenotype associations, we conducted a series of clinical examinations, including blood tests, brain MRI scans, ultrasound imaging, and ophthalmologic examination. Genomic DNA was extracted from the peripheral blood of the six‐person family, and the pathogenic variants were detected by whole‐exome sequencing (WES) and verified by Sanger sequencing. WES revealed two novel compound heterozygous variants in CPLANE1 : c.1270C>T (p.Arg424*) in exon 10 and c.8901C>A (p.Tyr2967*) in exon 48 of one child, inherited from each parent. Both variants were absent in ethnically matched Chinese control individuals and were either absent or present at very low frequencies in public databases, suggesting that these variants could be the pathogenic triggers of the JS phenotype. Notably, these CPLANE1 sequence variants were related to the pathogenesis of autosomal recessive JS in this study. The newly discovered variants expand the mutation spectrum of CPLANE1 , which assists in understanding the molecular mechanism underlying JS and improving the recognition of genetic counseling, particularly for families with a history of autosomal recessive JS.

Zhang, Cheng↗
DOE OSTI2023

Novel machine-learning method for spin classification of neutron resonances

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit resonant structure whose shape is determined in part by the angular-momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is, therefore, paramount. In this project, we apply machine learning to automate the quantum number assignments using only the resonances' energies and widths and not relying on detailed transmission or capture measurements. The classifier used for quantum number assignment is trained using stochastically generated resonance sequences whose distributions mimic those of real data. Here we explore the use of several physics-motivated features for training our classifier. These features amount to out-of-distribution tests of a given resonance's widths and resonance-pair spacings. We pay special attention to situations where either capture widths cannot be trusted for classification purposes or where there is insufficient information to classify resonances by the total spin J. We demonstrate the efficacy of our classification approach using simulated and actual 52 Cr resonance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 2. Evaluating Controls on Flow Persistence in an Urbanized Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in an urbanized catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, distributed temperature sensing (DTS), continuous self-potential (SP) monitoring, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Field_Application subfolder contains the ATS XML input scripts, data files, output data for the SP site. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. The flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.m can only be used with COMSOL with MATLAB) is executed using the ATS output data to simulate the potential field. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) DTS Contains collated DTS data including raw Stokes and anti-Stokes measurement (provided as .h5 file). It also includes DTS processing.ipynb, a Jupyter notebook for calibrating the DTS data using dts_calibration Python package. cooler_calibration.csv is the DTS calibration CSV used in the calibration sequence. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion. 6) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 7) SP Contains the SP data collected in field at the SP sites (provided as CSV files). 8) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). Note: Code files (.ipynb, .py, .xml) can be opened in any standard code editor, .exo file can be viewed using Paraview, .h5 files can be opened using HDFView software and h5py Python package, and .resipy file can be opened with the open-source ResIPy software.

ATS↗
DOE OSTI2023

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗
NASA NTRS1974

Automated Firearms Identification System (AFIDS), phase 1

Items critical to the future development of an automated firearms identification system (AFIDS) have been examined, with the following specific results: (1) Types of objective data, that can be utilized to help establish a more factual basis for determining identity and nonidentity between pairs of fired bullets, have been identified. (2) A simulation study has indicated that randomly produced lines, similar in nature to the individual striations on a fired bullet, can be modeled and that random sequences, when compared to each other, have predictable relationships. (3) A schematic diagram of the general concept for AFIDS has been developed and individual elements of this system have been briefly tested for feasibility. Future implementation of such a proposed system will depend on such factors as speed, utility, projected total cost and user requirements for growth. The success of the proposed system, when operational, would depend heavily on existing firearms examiners.

Blackwell, R. J.↗
NASA NTRS1974

Development status of solid polymer electrolyte water electrolysis for manned spacecraft life support systems

Details of the design and system verification test results are presented for a six-man-rated oxygen generation system. The system configuration incorporates components and instrumentation for computer-controlled operation with automatic start-up/shutdown sequencing, fault detection and isolation, and with self-contained sensors and controls for automatic safe emergency shutdown. All fluid and electrical components, sensors, and electronic controls are designed to be easily maintainable under zero-gravity conditions. On-board component spares are utilized in the system concept to sustain long-term operation (six months minimum) in a manned spacecraft application. The system is centered on a 27-cell solid polymer electrolyte water electrolysis module which, combined with the associated system components and controls, forms a total system envelope 40 in. high, 40 in. wide, and 30 in. deep.

Nuttall, L. J.↗
NASA NTRS1981

A Module Experimental Process System Development Unit (MEPSDU)

Design work for a photovoltaic module, fabricated using single crystal silicon dendritic web sheet material, resulted in the identification of surface treatment to the module glass superstrate which improved module efficiencies. A final solar module environmental test, a simulated hailstone impact test, was conducted on full size module superstrates to verify that the module's tempered glass superstrate can withstand specified hailstone impacts near the corners and edges of the module. Process sequence design work on the metallization process selective, liquid dopant investigation, dry processing, and antireflective/photoresist application technique tasks, and optimum thickness for Ti/Pd are discussed. A noncontact cleaning method for raw web cleaning was identified and antireflective and photoresist coatings for the dendritic webs were selected. The design of a cell string conveyor, an interconnect feed system, rolling ultrasonic spot bonding heat, and the identification of the optimal commercially available programmable control system are also discussed. An economic analysis to assess cost goals of the process sequence is also given.

Source record↗
NASA NTRS1987

Empirical models for use in designing decompression procedures for space operations

Empirical models for predicting the incidence of Type 1 altitude decompression sickness (DCS) and venous gas emboli (VGE) during space extravehicular activity (EVA), and for use in designing safe denitrogenation decompression procedures are developed. The models are parameterized using DCS and VGE incidence data from NASA and USAF manned altitude chamber decompression tests using 607 male and female subject tests. These models, and procedures for their use, consist of: (1) an exponential relaxation model and procedure for computing tissue nitrogen partial pressure resulting from a specified prebreathing and stepped decompression sequence; (2) a formula for calculating Tissue Ratio (TR), a tissue decompression stress index; (3) linear and Hill equation models for predicting the total incidence of VGE and DCS attendant with a particular TR; (4) graphs of cumulative DCS and VGE incidence (risk) versus EVA exposure time at any specified TR; and (5) two equations for calculating the average delay period for the initial detection of VGE or indication of Type 1 DCS in a group after a specific denitrogenation decompression procedure. Several examples of realistic EVA preparations are provided.

Conkin, Johnny↗