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DOE OSTI2020

Assessing the Additional Carbon Savings with Biofuel

A recent study claims that corn used for ethanol should not be considered to be inherently biogenically carbon-neutral because not all that corn was grown additional to the level otherwise. By assessing the extent of carbon neutrality of corn for ethanol using the reference point baseline approach and historical data that study concluded that the carbon intensity of US corn ethanol is 27% higher than that of gasoline. We develop a framework to determine the carbon neutrality of corn for ethanol by assessing the additional carbon uptake by crops using an anticipated baseline approach. We also apply this framework to determine the additional corn produced for ethanol and include the direct life cycle carbon emissions of only that portion of corn in the direct life cycle carbon intensity of corn ethanol. We implement this framework by integrating an economic model of the agricultural sector in the USA with a biogenic carbon model and life cycle analysis to quantify biogenic carbon uptake and direct life cycle emissions with and without corn ethanol expansion over the 2007–2027 period. We find that the combined biogenic carbon emissions and direct life cycle carbon emission intensity of corn ethanol (not including indirect land use related emissions) is 21% lower than gasoline. In conclusion, the lower value of this carbon intensity of corn ethanol compared with gasoline is robust to a wide range of parametric assumptions.

09 BIOMASS FUELS↗

NASA NTRS2007

Extravehicular Activity System Sizing Analysis Tool (EVAS_SAT)

An effort was initiated by NASA/JSC in 2001 to develop an Extravehicular Activity System Sizing Analysis Tool (EVAS_SAT) for the sizing of Extravehicular Activity System (EVAS) architecture and studies. Its intent was to support space suit development efforts and to aid in conceptual designs for future human exploration missions. Its basis was the Life Support Options Performance Program (LSOPP), a spacesuit and portable life support system (PLSS) sizing program developed for NASA/JSC circa 1990. EVAS_SAT estimates the mass, power, and volume characteristics for user-defined EVAS architectures, including Suit Systems, Airlock Systems, Tools and Translation Aids, and Vehicle Support equipment. The tool has undergone annual changes and has been updated as new data have become available. Certain sizing algorithms have been developed based on industry standards, while others are based on the LSOPP sizing routines. The sizing algorithms used by EVAS_SAT are preliminary. Because EVAS_SAT was designed for use by members of the EVA community, subsystem familiarity on the part of the intended user group and in the analysis of results is assumed. The current EVAS_SAT is operated within Microsoft Excel 2003 using a Visual Basic interface system.

Brown, Cheryl B.↗

NASA NTRS2010

Chiral Biomarkers and Microfossils in Carbonaceous Meteorites

Homochirality of the biomolecules (D-sugars of DNA and RNA and L-amino acids of proteins) is a fundamental property of all life on Earth. Abiotic mechanisms yield racemic mixtures (D/L=1) of chiral molecules and after the death of an organism, the enantiopure chiral biomolecules slowly racemize. Several independent investigators have now established that the amino acids present in CI1 and CM2 carbonaceous meteorites have a moderate to strong excess of the L-enantiomer. Stable isotope data have established that these amino acids are both indigenous and extraterrestrial. Carbonaceous meteorites also contain many other strong chemical biomarkers including purines and pyrimidines (nitrogen heterocycles of nucleic acids); pristine and phytane (components of the chlorophyll pigment) and morphological biomarkers (microfossils of filamentous cyanobacteria). Energy dispersive X-ray Spectroscopy (EDS) analysis reveals that nitrogen is below the detectability level in most of the meteorite filaments as well as in Cambrian Trilobites and filaments of 2.7 Gya Archaean cyanobacteria from Karelia. The deficiency of nitrogen in the filaments and the total absence of sugars, of twelve of the life-critical protein amino acids, and two of the nucleobases of DNA and RNA provide clear and convincing evidence that these filaments are not modern biological contaminants. This paper reviews the chiral, chemical biomarkers morphological biomarkers and microfossils in carbonaceous meteorites. This paper reviews chiral and morphological biomarkers and discusses the missing nitrogen, sugars, protein amino acids, and nucleobases as ?bio-discriminators? that exclude modern biological contaminants as a possible explanation for the permineralized cyanobacterial filaments found in the meteorites.

Hoover, Richard B.↗

NASA NTRS1995

Summary of EOS flight dynamics analysis

From a flight dynamics perspective, the Earth Observing System (EOS) spacecraft present a number of challenges to mission designers. The Flight Dynamics Support Branch of NASA GSFC has examined a number of these challenges, including managing the EOS constellation, disposing of the spacecraft at the end-of-life (EOL), and achieving the appropriate mission orbit given launch vehicle and ascent propulsion constraints. The EOS program consists of a number of spacecraft including EOS-AM, an ascending node spacecraft, EOS-PM, a descending node spacecraft, the EOS Chemistry mission (EOS-CHEM), the EOS Altimetry Laser (EOS-LALT), and the EOS-Altimetry Radar (EOS-RALT). The orbit characteristics of these missions are presented. In order to assure that downlinking data from each spacecraft will be possible without interference between any two spacecraft, a careful examination of the relationships between spacecraft and how to maintain the spacecraft in a configuration which would minimize these communications problems must be made. The FDSB has performed various analyses to determine whether the spacecraft will be in a position to interfere with each other, how the orbit dynamics will change the relative positioning of the spacecraft over their lifetimes, and how maintenance maneuvers could be performed, if needed, to minimize communications problems. Prompted by an activity at NASA HQ to set guidelines for spacecraft regarding their end-of-life dispositions, much analysis has also been performed to determine the spacecraft lifetime of EOS-AM1 under various conditions, and to make suggestions regarding the spacecraft disposal. In performing this analysis, some general trends have been observed in lifetime calculations. The paper will present the EOS-AM1 lifetime results, comment on general reentry conclusions, and discuss how these analyses reflect on the HQ NMI. Placing the EOS spacecraft into their respective mission orbits involves some intricate maneuver planning to assure that all mission orbit requirements are met, given the initial conditions supplied by the launch vehicle at injection. The FDSB has developed an ascent scenario to meet the mission requirements. This paper presents results of the ascent analysis.

Newman, Lauri Kraft↗

NASA NTRS1994

How long did it take for life to begin and evolve to cyanobacteria?

There is convincing paleontological evidence showing that stromatolite-building phototactic prokaryotes were already in existence 3.5 x 10(9) years ago. Late accretion impacts may have killed off life on our planet as late as 3.8 x 10(9) years ago. This leaves only 300 million years to go from the prebiotic soup to the RNA world and to cyanobacteria. However, 300 million years should be more than sufficient time. All known prebiotic reactions take place in geologically rapid time scales, and very slow prebiotic reactions are not feasible because the intermediate compounds would have been destroyed due to the passage of the entire ocean through deep-sea vents every 10(7) years or in even less time. Therefore, it is likely that self-replicating systems capable of undergoing Darwinian evolution emerged in a period shorter than the destruction rates of its components (<5 million years). The time for evolution from the first DNA/protein organisms to cyanobacteria is usually thought to be very long. However, the similarities of many enzymatic reactions, together with the analysis of the available sequence data, suggest that a significant number of the components involved in basic biological processes are the result of ancient gene duplication events. Assuming that the rate of gene duplication of ancient prokaryotes was comparable to today's present values, the development of a filamentous cyanobacterial-like genome would require approximately 7 x 10(6) years--or perhaps much less. Thus, in spite of the many uncertainties involved in the estimates of time for life to arise and evolve to cyanobacteria, we see no compelling reason to assume that this process, from the beginning of the primitive soup to cyanobacteria, took more than 10 million years.

Non-NASA Center↗

NASA NTRS2008

The Mars Phoenix Thermal Evolved-Gas Analysis: The Role of an Organic Free Blank in the Search for Organics

The Thermal Evolved-Gas Analyzer (TEGA) instrument onboard the 2007 Phoenix Lander will perform differential scanning calorimetry (DSC) and evolved-gas analysis of soil samples collected from the surface. Data from the instrument will be compared with Mars analog mineral standards, collected under TEGA Mars-like conditions to identify the volatile-bearing mineral phases [1] (e.g., Fe-oxyhydroxides, phyllosilicates, carbonates, and sulfates) found in the Martian soil. Concurrently, the instrument will be looking for indications of organics that might also be present in the soil. Organic molecules are necessary building blocks for life, although their presence in the ice or soil does not indicate life itself. The spacecraft will certainly bring organic contaminants to Mars even though numerous steps were taken to minimize contamination during the spacecraft assembly and testing. It will be essential to distinguish possible Mars organics from terrestrial contamination when TEGA instrument begins analyzing icy soils. To address the above, an Organic Free Blank (OFB) was designed, built, tested, and mounted on the Phoenix spacecraft providing a baseline for distinguishing Mars organics from terrestrial organic contamination. Our objective in this report is to describe some of the considerations used in selecting the OFB material and then report on the processing and analysis of the final candidate material

Lauer, H. V., Jr.↗

DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Unraveling the Threads of Environmental Justice in Critical Mineral Extraction: A Framework for Regionalized Life Cycle Data

As we transition to a more sustainable energy system, the extraction and processing of critical minerals becomes increasingly important. However, these industries often raise concerns about environmental and social impacts, particularly in disadvantaged communities. To address these concerns, our research focuses on regionalizing environmental life cycle data to connect it with communities affected by mineral extraction. A framework was developed for collecting life cycle background data that supports the Justice40 Toolset, a market-based approach to evaluating net benefits and costs of critical mineral material recovery pathways. A goal was to alleviate public skepticism around mineral extraction processes, including secondary and unconventional feedstocks, by highlighting both environmental and social impacts. To achieve this, computational analysis and geospatial data science techniques were employed, such as within-scale and across-scale methods and proxy dataset usage. By doing so, we were able to develop a framework for identifying and disaggregating data down to regions small enough to support Justice40 goals. Our approach not only provides valuable tools fo insight into the environmental implications of mineral extraction but also helps policymakers evaluate the social impacts on local communities. This research contributes to a more just and equitable transition to a sustainable energy system, ensuring that marginalized voices are heard in decision-making process.

Davis, Tyler [NETL Site Support Contractor, Nation↗

DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Assessment of NuScale SMR Steam Heat Augmentation for Chemical Plant Decarbonization

Nearly 50% of the total energy consumed by the industrial sector in the United States is used to produce process steam with natural gas and coal-fired boilers1 . This project conducts a technoeconomic assessment of a NuScale Small Modular Reactor (SMR) coupled with a chemical plant as an Integrated Energy System (IES) where nuclear produces steam and electric power to meet the requirements of a large chemical plant. In a 2020 study, ORNL evaluated the feasibility of using advanced SMRs, including the NuScale design, to supply energy to the Eastman Chemical Plant. However, since that report was published, NuScale received NRC approval for its uprated 77 MWe design with 56% more power and has also introduced a high-temperature, high pressure, steam heat-augmentation system, a key focus of the new study. The new study also benefits from revised capital costs, a 10-day refueling outage time, reduced plant staffing, higher capacity factors, and a site boundary Emergency Planning Zone methodology. The study consists of a techno-economic assessment of two possible energy sources (nuclear and natural gas) in a number of steam and power generation configurations (NuScale Power Modules (NPMs), boilers and combinations of both) to satisfy the steam and power demand with the most reliable and cost competitive system. A total of 2,947.3 klb/hr of steam and 72.5 MWe of electricity are required for the demonstration case. A range of scenarios and solutions are explored, from a 12-NPM plant (3,000 MWth)—with excess capacity and redundancy, capable of supplying a significant amount of extra power to the grid—to a 4-NPM (1,000 MWth) plant—supplemented with existing boilers or grid power for redundancy. The study uses historical steam and power data from a chemical plant and examines the sensitivity to natural gas and grid power cost variations. Scenarios with up to two times gas and electricity costs were considered. Profitability in a 60-year time horizon was analyzed, consistent with NuScale’s design life specification. A steady-state site integration and reliability analysis was performed, and trade-offs were identified.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1989

Finite element analysis of the Space Shuttle Main Engine (SSME) high pressure fuel turbopump turbine blade (HPFTP)

Cracking of the turbine blades of the SSME HPFTP is studied using two- and three-dimensional finite element analysis. The development and composition of the two- and three-dimensional models are described. Analyses are conducted under the speed, pressure, and thermal load conditions that occur during the full power level of the engine. The effects of friction on the two-dimensional model are examined. The strain and life cycle data reveal that the LCF cracking in the first stage is not probable unless the effects of fit-up tolerance between the blade and rotor are present, and for the second stage it is predicted that hydrogen assisted LCF cracking will occur under the present thermal environment. Design modifications to alleviate this cracking are discussed.

Lee, H. M.↗

NASA NTRS1991

Taurus lightweight manned spacecraft Earth orbiting vehicle

The Taurus Lightweight Manned Spacecraft (LMS) was developed by students of the University of Maryland's Aerospace Engineering course in Space Vehicle Design. That course required students to design an Alternative Manned Spacecraft (AMS) to augment or replace the Space Transportation System and meet the following design requirements: (1) launch on the Taurus Booster being developed by Orbital Sciences Corporation; (2) 99.9 percent assured crew survival rate; (3) technology cutoff data of 1 Jan. 1991; (4) compatibility with current space administration infrastructure; and (5) first flight by May 1995. The Taurus LMS design meets the above requirements and represents an initial step towards larger and more complex spacecraft. The Taurus LMS has a very limited application when compared to the Space Shuttle, but it demonstrates that the U.S. can have a safe, reliable, and low cost space system. The Taurus LMS is a short mission duration spacecraft designed to place one man into low earth orbit (LEO). The driving factor for this design was the low payload carrying capabilities of the Taurus Booster--1300 kg to a 300 km orbit. The Taurus LMS design is divided into six major design sections. The human factors system deals with the problems of life support and spacecraft cooling. The propulsion section contains the abort system, the Orbital Maneuvering System (OMS), the Reaction Control System (RCS), and power generation. The thermal protection systems and spacecraft structure are contained in the structures section. The avionics section includes navigation, attitude determination, data processing, communication systems, and sensors. The mission analysis section was responsible for ground processing and spacecraft astrodynamics. The systems integration section pulled the above sections together into one spacecraft and addressed costing and reliability.

Chase, Kevin A.↗

NASA NTRS1991

Taurus Lightweight Manned Spacecraft Earth orbiting vehicle

The Taurus Lightweight Manned Spacecraft (LMS) was developed by students of the University of Maryland's Aerospace Engineering course in Space Vehicle Design. That course required students to design an Alternative Manned Spacecraft (AMS) to augment or replace the Space Transportation System and meet the following design requirements: (1) launch on the Taurus Booster being developed by Orbital Sciences Corporation; (2) 99.9 percent assured crew survival rate; (3) technology cutoff date of 1 Jan. 1991; (4) compatibility with current space administration infrastructure; and (5) first flight by May 1995. The Taurus LMS design meets the above requirements and represents an initial step toward larger and more complex spacecraft. The Taurus LMS has a very limited application when compared to the space shuttle, but it demonstrates that the U.S. can have a safe, reliable, and low-cost space system. The Taurus LMS is a short mission duration spacecraft designed to place one man into low Earth orbit (LEO). The driving factor for this design was the low payload carrying capabilities of the Taurus Booster - 1300 kg to a 300-km orbit. The Taurus LMS design is divided into six major design sections. The Human Factors section deals with the problems of life support and spacecraft cooling. The Propulsion section contains the Abort System, the Orbital Maneuvering System (OMS), the Reaction Control System (RCS), and Power Generation. The thermal protection systems and spacecraft structure are contained in the Structures section. The Avionics section includes Navigation, Attitude Determination, Data Processing, Communication systems, and Sensors. The Mission Analysis section was responsible for ground processing and spacecraft astrodynamics. The Systems Integration Section pulled the above sections together into one spacecraft, and addressed costing and reliability.

Bosset, M.↗

NASA NTRSDate not supplied

RNASeq and Fluorescence Analysis of the Response of ERF2 and ERF104 in Arabidopsis thaliana under Simulated Altered Gravity

As NASA moves closer to long-term human space exploration, the need to understand how to sustain life in space is increasingly pressing. Plants are essential to human sustenance, making it important to understand how spaceflight affects plant health. We used differential gene expression analysis to examine GLDS-251 (RNAseq analysis of the response of Arabidopsis thaliana to fractional gravity under blue-light stimulation during spaceflight) from NASA’s GeneLab data repository and found downregulation of ERF2 and ERF104, transcription factors of the ethylene response factor families, that integrate hormonal pathways involved in abiotic stress responses. Downregulation of ERF2 and ERF104 during spaceflight may indicate a dysregulation of the ethylene signaling pathway. Our hypothesis is that altered gravity downregulates the expression of ERF2 and ERF104 in Arabidopsis thaliana, altering the ethylene signaling pathway and affecting the electron transport chain and light-dependent reactions in chloroplast thylakoids. To test this hypothesis, we propose to grow A. thaliana seedlings (wild-type and mutant/knockout of ERF2 and ERF104) in altered gravity conditions to determine the effects on the expression of ERF2, ERF104, and photosynthesis. We anticipate that ERF2 and ERF104 will be underexpressed in altered gravity conditions and result in decreased regulation of the ethylene signaling pathway.

Arabidopsis↗

NASA NTRS2003

Multi-Disciplinary Analysis for Future Launch Systems Using NASA's Advanced Engineering Environment (AEE)

A new engineering environment constructed for the purposes of analyzing and designing Reusable Launch Vehicles (RLVs) is presented. The new environment has been developed to allow NASA to perform independent analysis and design of emerging RLV architectures and technologies. The new Advanced Engineering Environment (AEE) is both collaborative and distributed. It facilitates integration of the analyses by both vehicle performance disciplines and life-cycle disciplines. Current performance disciplines supported include: weights and sizing, aerodynamics, trajectories, propulsion, structural loads, and CAD-based geometries. Current life-cycle disciplines supported include: DDT&E cost, production costs, operations costs, flight rates, safety and reliability, and system economics. Involving six NASA centers (ARC, LaRC, MSFC, KSC, GRC and JSC), AEE has been tailored to serve as a web-accessed agency-wide source for all of NASA's future launch vehicle systems engineering functions. Thus, it is configured to facilitate (a) data management, (b) automated tool/process integration and execution, and (c) data visualization and presentation. The core components of the integrated framework are a customized PTC Windchill product data management server, a set of RLV analysis and design tools integrated using Phoenix Integration's Model Center, and an XML-based data capture and transfer protocol. The AEE system has seen production use during the Initial Architecture and Technology Review for the NASA 2nd Generation RLV program, and it continues to undergo development and enhancements in support of its current main customer, the NASA Next Generation Launch Technology (NGLT) program.

Monell, D.↗

NASA NTRS2011

Space Radiation Effects on Human Cells: Modeling DNA Breakage, DNA Damage Foci Distribution, Chromosomal Aberrations and Tissue Effects

Future long-tem space travel will face challenges from radiation concerns as the space environment poses health risk to humans in space from radiations with high biological efficiency and adverse post-flight long-term effects. Solar particles events may dramatically affect the crew performance, while Galactic Cosmic Rays will induce a chronic exposure to high-linear-energy-transfer (LET) particles. These types of radiation, not present on the ground level, can increase the probability of a fatal cancer later in astronaut life. No feasible shielding is possible from radiation in space, especially for the heavy ion component, as suggested solutions will require a dramatic increase in the mass of the mission. Our research group focuses on fundamental research and strategic analysis leading to better shielding design and to better understanding of the biological mechanisms of radiation damage. We present our recent effort to model DNA damage and tissue damage using computational models based on the physics of heavy ion radiation, DNA structure and DNA damage and repair in human cells. Our particular area of expertise include the clustered DNA damage from high-LET radiation, the visualization of DSBs (DNA double strand breaks) via DNA damage foci, image analysis and the statistics of the foci for different experimental situations, chromosomal aberration formation through DSB misrepair, the kinetics of DSB repair leading to a model-derived spectrum of chromosomal aberrations, and, finally, the simulation of human tissue and the pattern of apoptotic cell damage. This compendium of theoretical and experimental data sheds light on the complex nature of radiation interacting with human DNA, cells and tissues, which can lead to mutagenesis and carcinogenesis later in human life after the space mission.

Ponomarev, A. L.↗

NASA NTRS1988

Analysis and reconstruction of helicopter load spectra

Notched metal test samples are presently subjected to helicopter load histories and the results obtained are compared to the fatigue-life predictions of a simplified version of the local-strain method. After studying the case of a peak/valley reconstructed history based on the standard spectrum, attention is given to a second, more irregular one based on actual flight data which is used to generate three reconstructed histories based on peak-valley, to-from, and rainflow characteristics. Comparisons indicate the rainflow cycle approach to be the most promising.

Khosrovaneh, A. K.↗

DOE OSTI2021

A machine learning degradation model for electrochemical capacitors operated at high temperature

Electrochemical capacitors (ECs) have only recently been considered as an alternative power source for telemetry sensors of drilling equipment for geothermal or oil and gas exploration. The lifecycle analysis and modelling of ECs is underrepresented in literature in comparison to other storage devices e.g. Li-ion batteries. This paper investigates the degradation of ECs when cycled outside the manufacturer-specified operating temperature envelope and proposes a machine learning-based approach for modelling the degradation. Experimental results show that end of life, defined as a 30% decrease in capacitance, occurs at 1,000 cycles when the environmental temperature exceeds the maximum operating temperature by 30%. The life-cycle test data is then used as an input to a Gaussian process regression (GPR) algorithm to predict the capacitance fade trend. The GPR is validated on a total of nine commercial cells from two different manufacturers, achieving an average root mean squared percent error of less than 2% and a mean calibration score of 93% when referenced to a 95% confidence interval. The model can be utilized to determine the EC degradation rate at a range of operating temperature values.

42 ENGINEERING↗