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DOE OSTI2022

The Science of Scientific Software Development and Use

Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them is often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. The US Department of Energy Office of Science (DOE-SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. In December 2021, the DOE-SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: software has become an essential part of modern science that impacts new discovery, policy, and technological development. To have full confidence in science delivered via software, we must improve the processes and tools that help us create and use it, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work. The full workshop report will be available at https://doi.org/10.2172/1846009.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Basic Research Needs in The Science of Scientific Software Development and Use: Investment in Software is Investment in Science

Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them are often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. Increased investment, especially in the characterization and improvement of how scientific software is developed and used, is important for sustaining and improving the impact of software as the scope and complexity of scientific efforts expand. Without this investment, we face the risk of diminishing returns on our software investments because the demands for increased functionality, usability, reliability, and more will not be sufficiently met. The US Department of Energy Office of Science (DOE/SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. For many years, DOE/SC software investments have provided tremendous value to the scientific community. We want to continue and further improve the value of DOE/SC software efforts by using a scientific approach to understanding and improving how scientific software is developed and used. In December 2021, the DOE/SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific-Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, which built on insights from 124 pre-workshop position papers, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: Software has become an essential part of modern science, impacting discoveries, policy, and technological development. To maintain and improve confidence in science delivered via software, we must improve the processes and tools that help us create and use software, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Energy Storage for Social Equity Roundtable Report

In support of the Office of Electricity Energy Storage program, Pacific Northwest National Laboratory (PNNL), hosted a roundtable to explore the relationship between energy equity and energy storage. Flexible and available at any scale, energy storage offers a useful framework and starting point in a larger conversation around energy equity. Through storage, we can imagine more broadly how improvements and investments in the grid can respond to social and health challenges and increase affordability, reliability, and community value in the future. The roundtable featured keynotes and conversations with people leading the charge in transitioning our energy system to a more equitable, affordable, accessible, and sustainable future. This event was presented in collaboration with Sandia National Laboratories.

25 ENERGY STORAGE↗
DOE OSTI2021

Report on Next-Gen AI for Proliferation Detection Workshop: Domain-Aware Methods

The emergence of artificial intelligence (AI) and machine learning (ML) in the modern world has impacted nearly every application imaginable. This includes nuclear proliferation detection, which offers the potential to improve existing capabilities as well as create new ones. Proliferation detection seeks to detect and characterize attempts by state and non-state actors to acquire nuclear weapons or associated technology, materials, or knowledge. Such a mission is vitally important for global stability and security but is notoriously difficult. By leveraging advances in AI, exciting opportunities exist to enhance the proliferation detection regime. The Data Science and AI portfolio within the National Nuclear Security Administration’s Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D) seeks to leverage the capabilities of the Department of Energy’s (DOE’s) national laboratories and other partners to develop AI systems that can accomplish otherwise impossible tasks in support of proliferation detection. As part of its efforts, the portfolio has created a series of workshops on Next-Gen AI for Proliferation Detection to help define the requirements for suitable AI systems, share successful research and best practices, and foster connection and understanding between the relevant parties including researchers and end-users. Each workshop in the series focuses on a specific and critical aspect of AI to enable it to accomplish proliferation detection objectives. The first workshop focused on explainability techniques; the second workshop and the topic of this report, covers methods for incorporating domain awareness into AI. The Next-Gen AI for Proliferation Detection Workshop: Domain-Aware Methods took place virtually over two days in February 2021 and included four keynote presentations, 22 technical presentations, and a concluding panel. The presentations, discussions, and workshop findings are summarized in this report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Bioimaging Science Program Principal Investigator Meetings Proceedings (2021)

As part of the 2021 Biological Systems Science Division (BSSD) Principal Investigator (PI) Meeting, the Bioimaging Science program (BSP), within BSSD's Biomolecular Characterization and Imaging Science portfolio, held its annual PI meeting virtually February 22–23. BSP's mission is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. BSP convenes annual PI meetings to bring together its contributing investigators to review progress and current state-of-the-art bioimaging research. Holding the BSP meeting as part of the broader BSSD PI meeting allowed researchers to interact with the extended Genomic Science program community. This convergence provided a platform for networking and exchange of ideas, helping to forge new multidisciplinary collaborations among investigators from the two sister programs. An important highlight of the BSP meeting was the keynote presentation “Enhancing Fluorescence Microscopy with Computation” by Dr. Hari Shroff of the NIH National Institute of Biomedical Imaging and Bioengineering. All the BSP PIs made presentations describing their research focus and progress, and these were followed by roundtable discussions of each project. The meeting’s proceedings provide an outline of the program’s current state and potential future directions and opportunities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Bioimaging Science Program: 2022 Principal Investigator Meetings Proceedings

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Safety in Artificial Intelligence: Challenges and Opportunities for the U.S. National Labs and Beyond

This report discusses the importance of the critical and underexplored topic of artificial intelligence (AI) safety, as highlighted during the “Strategy Alignment on AI Safety” workshop convened at Lawrence Livermore National Laboratory (LLNL) in April 2024. Through a summary of keynote talks, panel discussions, and breakout sessions, world-leading AI safety experts from academic, industry, national labs, and government agencies clearly agree on the need for and importance of large-scale investments for research and capabilities in AI safety. With the field innovating at unprecedented rates, there is increasing urgency to develop novel evaluation methodologies that allow full considerations of risks/threats of AI technologies in different domains. Quantitative metrics and effective methodologies that can evaluate and audit the “safeness” of how a given AI technology is trained, deployed, or regulated are, at best, nascent for certain scenarios or, more commonly, nonexistent. This maturation gap presents the possibility of serious threats to national security, and further inaction may have serious consequences. Additionally, the gap between the public’s and research community’s perceptions of AI risks/rewards is significant. While numerous voices from the AI community have expressed concern that the risks could be so high that future AI systems could inflict extinction-level damage to humanity if deployed incorrectly, the public largely is aware only of risk in low-impact scenarios. This discrepancy highlights the crucial need for researchers to articulate to governmental bodies what, why, and when various AI risks matter as part of motivating funding requests. Thus, the call to action for this community is to pursue AI safety as a “Big Science” project on a scale comparable to the Manhattan Project. High risks and high payoffs are on the table, but safe AI is a fast-moving target, and large-scale investments are needed to guide development of this technology in a responsible way. We highlight the need for a multilayered solution combining the development of new methods and algorithmic approaches to mitigate threats with an active participation of the government(s) in setting high industry standards and regulations based on state-of-the-art technology. The U.S. Department of Energy (DOE) national laboratories have served as leading institutions for scientific innovation in the U.S. for more than 70 years. Drawing on their expertise in the AI community and their history of safeguarding critical and sensitive information, and as we look to the future, national labs are the best choice for evaluating and safeguarding AI technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Overview of NETL’s Low Temperature CO2 Electrolysis Research

This keynote lecture will briefly overview diverse research areas of National Energy Technology Laboratory (NETL) to advance energy and environmental sustainability along with carbon management. Our electrochemistry efforts on carbon conversion directly support the US goal of achieving carbon-free power sector by 2035 and net zero emissions by 2050. Since CO2 electroreduction is highly structure-sensitive, NETL ongoing research has been focused on the rational design and engineering of electrocatalysts to facilitate the CO2 conversion to desirable products with good selectivity, activity, and durability. Different classes and types of electrocatalytic materials will be covered in this talk, from well-defined atomic-scale model catalysts to heterogenous, scalable powder systems at nano- and micro-scale for “real world” performance evaluation. Several spectroscopic, microscopic, and electrochemical characterization techniques along with computational findings will be additionally discussed to gain more insights into the structure-activity relation. The last part of this seminar will provide more detail on how NETL has transitioned from the most common aqueous H-type reactor for lab-scale validation to more realistic full electrolyzer cell in bench-scale prototype. The knowledge, electrocatalytic materials, and device validation achieved from NETL in-house research will be translated to industrial sector for large scale deployment and the anticipated outcome will help advance the development of low temperature CO2 electrolysis technologies.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

Power Technologies for Rail Decarbonization Workshop: Summary Report

Argonne National Laboratory organized the Power Technologies for Rail Decarbonization Workshop for the U.S. Department of Energy (DOE) Vehicle Technologies Office. The workshop offered an inclusive venue for different stakeholders to convey their perspective on challenges and opportunities in decarbonizing the rail sector. The first day of the workshop focused on (1) rail decarbonization efforts in the DOE and collaboration opportunities, (2) technology pathways to decarbonize rail, and (3) prime mover and low-carbon options for rail. The second day was devoted to (1) prime mover and zero-carbon options for rail, and (2) rail logistics, infrastructure, and safety. Each day raised challenges and solutions through presentations from national leaders and discussions among panel members and the audience. Through this engagement with different stakeholders, we will produce a cross-disciplinary recommendation for the role of government agencies to contribute meaningful research to address current technology gaps. The workshop included up 139 active participants and featured keynote speakers and panelists from Association of American Railroads, Progress Rail Locomotive, Wabtec, Burlington Northern Santa Fe Railroad, Amtrak, Caterpillar, Cummins, Renewable Energy Group-Chevron, DOE’s Bioenergy Technologies Office, California Air Resources Board, Federal Railroad Administration and multiple DOE national laboratories. This summary report presents highlights from participant discussions covering the topics of technology pathways to decarbonize rail, prime mover and low-carbon options, prime mover and zero-carbon options, as well as rail logistics, infrastructure, and safety. The variety of input gathered from the stakeholder attendees is vital, as it helps inform DOE on rail decarbonization challenges and opportunities. Stakeholder feedback is balanced against DOE strategic directions and priorities with consideration of the roles of government and industry.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Intelligent Manufacturing for Extreme Environments Conference Proceedings

The Intelligent Manufacturing for Extreme Environments (IMEE) workshop was held at the Center for Advanced Energy Studies (CAES) in Idaho Falls, Idaho, May 2–3, 2023, in support of the United States (U.S.) National Science Foundation (NSF) Established Program to Stimulate Competitive Research: Workshop Opportunities (EPSCoR-WO) program. This workshop featured keynote speakers, panels, and breakout sessions with 58 participants. Nuclear reactors need to operate under extreme service conditions, such as high temperatures, corrosive environments, and high-radiation doses. Hence, reactor components must be able to withstand those conditions. The participants envision a future where on demand manufacture of components for small modular reactors (SMRs), microreactors, and other advanced reactor designs are possible. In this future, regulatory bodies accept validated manufacturing processes and standardized feedstocks, thus eliminating the need for individual component testing. However, the necessary technologies and regulatory policies needed for this future do not exist today. Successful innovation would revolutionize the nuclear power sector, enable fast commercial development, create economic opportunities in the U.S., reduce the carbon footprint and associated risks, and promote a skilled and highly competitive workforce. The objective of the workshop was to convene world-class experts, researchers, educators, and students to identify gaps and envision solutions for five interrelated challenges for intelligent manufacturing in extreme environments. The key outcomes of the conference were: (1) to take the opportunity for researchers and educators to network and form collaborations; and (2) to produce a full report to inform policy-makers, industry, and the academic community of various challenges and opportunities in the nuclear energy sector.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties

This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

2024 IUFRO Tree Biotechnology Conference (Aug 4-8, 2024)

The 2024 IUFRO Tree Biotechnology Conference is the biennial meeting on genomics, molecular biology, and biotechnology of forest trees, associated with the IUFRO Working Party 2.04.06. This year's meeting was held in Annapolis, MD, USA from August 4th to 8th and was hosted by Yiping Qi (University of Maryland), Edward Eisenstein (University of Maryland), Gary Coleman (University of Maryland), and Heather Coleman (Syracuse University). The conference covered seven topics over the course of five days: 1) Biological and ecological insights from OMICS, 2) Advancing technologies for targeted trait manipulation and acceptability to diverse tree species, 3) Genes, development, and physiology, 4) Translating genomics and biotechnology to practice, 5) Trees in a changing world, 6) Genetic and phenotypic diversity for breeding and genomic selection, and 7) Biotechnology for biomaterials and bioeconomy. In addition to the sessions, there were two plenary sessions, provided by John Ralph (University of Wisconsin) and Tanja Pyrhäjärvi (University of Helsinki). The meeting celebrated the second awardees of the newly created IUFRO WG 2.04.06 Award: Excellence in Forest Molecular Biology and Genomics, which was presented to Chung-Jui (C.J.) Tsai (University of Georgia). Greg Goralogia (Oregon State University) was the recipient of the associated Early Career Award. The scientific presentations at the conference highlighted cutting-edge advancements in many facets of forest biotechnology research, including applications of genomic selection in forest genetics and breeding, the use of genetic editing, tree physiology, stress response, molecular breeding, wood development, "omics" technologies, and the social and economic impacts of genetically modified (GM) trees. Scientific take homes from the meeting include the power of NMR to dissect the composition of lignin, the genomic diversity of forest trees that has enormous potential for tree improvement and the integration of systems biology with climate and geographical data. The conference attracted a mix of students (25), postdoctoral fellows (32), and scientists from academia (66) and industry (18). In all, the conference was attended by 141 registered participants, representing 20 countries that participated in 23 invited lectures (including 6 'early-career' keynotes), 27 voluntary talks and 61 poster presentations. Support for the conference was drawn from a wide variety of Academia, Industry, and Government sources, and included financial support from several tree improvement companies. Overall, the conference was a great success, providing an exceptional mix of science and social activities in a relaxed and collegial atmosphere. More information about the meeting can be found at treebiotech.org. The next meeting will be held in Stellenbosch, South Africa, in 2026, hosted jointly by Zander Myburg, Dave Drew (University of Stellenbosch,) and Sanushka Naidoo (University of Pretoria, FABI).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploring the Feasibility of INCONEL® ALLOY 740H® for Power Plant Headers: Integrating Machine Learning with Computational Fluid Dynamics (CFD)

This keynote presentation explores the behavior of headers—essential components of pipeline systems—using ANSYS simulation software and machine learning techniques. The study aims to predict the thermal and mechanical performance of headers under diverse conditions through both steady-state and transient simulations. We investigate critical parameters such as heat transfer coefficient, fluid velocity, and temperature to optimize header design. Conducted as part of a DOE project led by NCAT in collaboration with UNC Charlotte, this research encompasses multiple key topics. The initial section focuses on the behavior of header systems under steady-state conditions using ANSYS simulation. It underscores the importance of headers in industrial infrastructure, especially in the energy sector, and examines the implications of material selection and flow direction on heat transfer dynamics. Methodologically, we employ Computational Fluid Dynamics (CFD) analysis through ANSYS, detailing the development of models, material properties, geometry specifications, boundary conditions, and meshing strategies. Our simulations explore various operational parameters, including temperature and mass flow rates, crucial for predicting heat transfer coefficients and enhancing header design. Results from the study include parametric investigations into mesh sensitivity, viscosity model evaluations, and the effects of heat transfer locations, all validated against theoretical calculations. We conclude with insights on mesh optimization, the suitability of viscosity models, and recommendations for future research aimed at improving header system efficiency and sustainability in industrial applications.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Conference Support: 50th Midwest/Southeast Regional Photosynthesis Conference 2024

The DOE grant referenced above supported the 50th Anniversary Meeting of the Midwest/Southeast Regional Photosynthesis Conference, held at Turkey Run State Park, Marshall, Indiana, from October 25-27, 2024. The meeting featured four keynote speakers – Drs. Govindjee, Wim Vermaas, David Vinyard, and Lauren Metskas – and 12 oral presentations by student and postdoctoral trainees, selected from submitted abstracts. The meeting had a total attendance of 85 participants, including 62 students and research scientists. DOE funds were used to waive the registration fees for all students and trainees (totaling $\$$2,500) and to support seven travel awards of $\$$350 each, for a total of $\$$2,450. Each travel award covered food and accommodation for the recipient at Turkey Run State Park during the conference.

14 SOLAR ENERGY↗
DOE OSTI2023

Bioenergy’s Role in Soil Carbon Storage Decarbonizing Transportation, Agriculture, and Industrial Sectors Workshop Summary Report

On March 28–29, 2022, the U.S. Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) hosted the public virtual workshop “Bioenergy’s Role in Soil Carbon Storage.” Given the recent emphasis of the Biden administration on decarbonizing transportation, agriculture, and industrial sectors of the U.S. economy, this workshop examined how decarbonization through enhanced soil carbon storage while growing bioenergy crops is possible by discussing challenges and opportunities that affect soil carbon levels. Stakeholders representing academia, industry, the farming community, agricultural and forestry sectors, municipalities, and federal agencies involved in soil carbon storage participated in this workshop. A series of keynote presentations, plenary presentations, and stakeholder input sessions provided opportunities for sharing knowledge and identifying research and development (R&D) needs for future advances in soil carbon storage in relation to bioenergy crops. This document provides an overview of the content discussed in the presentations, as well as a summary of the stakeholder input received during the session discussions.

09 BIOMASS FUELS↗
NASA NTRS1981

The future of aeronautical propulsion

This keynote address discusses some of the future challenges and opportunities confronting aeronautics where propulsion is a key factor. The discussion covers various aircraft types including commercial transports, general aviation and military aircraft and identifies propulsion technology required to accommodate further advancements in these types of aircraft. This is then followed by a discussion of some of the emerging technologies that, if properly exploited, will have significant effect on the engines of the '90's. Some comments on further advancements in the traditional technologies are also included.

Stewart, W. L.↗
NASA NTRS1989

MEVTV Workshop on Tectonic Features on Mars

The state of knowledge of tectonic features on Mars was determined and kinematic and mechanical models were assessed for their origin. Three sessions were held: wrinkle ridges and compressional structure; strike-slip faults; and extensional structures. Each session began with an overview of the features under discussion. In the case of wrinkle ridges and extensional structures, the overview was followed by keynote addresses by specialists working on similar structures on the Earth. The first session of the workshop focused on the controversy over the relative importance of folding, faulting, and intrusive volcanism in the origin of wrinkle ridges. The session ended with discussions of the origin of compressional flank structures associated with Martian volcanoes and the relationship between the volcanic complexes and the inferred regional stress field. The second day of the workshop began with the presentation and discussion of evidence for strike-slip faults on Mars at various scales. In the last session, the discussion of extensional structures ranged from the origin of grabens, tension cracks, and pit-crater chains to the origin of Valles Marineris canyons. Shear and tensile modes of brittle failure in the formation of extensional features and the role of these failure modes in the formation of pit-crater chains and the canyons of Valles Marineris were debated. The relationship of extensional features to other surface processes, such as carbonate dissolution (karst) were also discussed.

Watters, Thomas R.↗