Search NASA⌕ Search

SEARCH · Search NASA

Results for “Resource characterization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,423 records · Page 79

Helical allophycocyanin nanotubes absorb far-red light in a thermophilic cyanobacterium

To compete in certain low-light environments, some cyanobacteria express a paralog of the light-harvesting phycobiliprotein, allophycocyanin (AP), that strongly absorbs far-red light (FRL). Using cryo–electron microscopy and time-resolved absorption spectroscopy, we reveal the structure-function relationship of this FRL-absorbing AP complex (FRL-AP) that is expressed during acclimation to low light and that likely associates with chlorophyll a–containing photosystem I. FRL-AP assembles as helical nanotubes rather than typical toroids due to alterations of the domain geometry within each subunit. Spectroscopic characterization suggests that FRL-AP nanotubes are somewhat inefficient antenna; however, the enhanced ability to harvest FRL when visible light is severely attenuated represents a beneficial trade-off. The results expand the known diversity of light-harvesting proteins in nature and exemplify how biological plasticity is achieved by balancing resource accessibility with efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

Utah FORGE: Well Data for Student Competition

Well 58-32 (previously labeled MU-ESW1) was drilled near Milford Utah during Phase 2B of the FORGE Project to confirm geothermal reservoir characteristics met requirements for the final FORGE site. Well Accord-1 was drilled decades ago for geothermal exploration purposes. While the conditions encountered in the well were not suitable for developing a conventional hydrothermal system, the information obtained suggested the region may be suitable for an enhanced geothermal system. Geophysical well logs were collected in both wells to obtain useful information regarding there nature of the subsurface materials. For the recent testing of 58-32, the Utah FORGE Project contracted with the well services company Schlumberger to collect the well logs.

15 GEOTHERMAL ENERGY↗

Utah FORGE: Wells Wow2 and Wow3 Groundwater Monitoring Data

This dataset includes ground water level data for Utah FORGE Phase 2c ground water monitoring wells Wow2 and Wow3. The readme file explains the fields contained in the included Excel spreadsheet and contains the coordinates for the wells. The Excel spreadsheet contains raw data taken directly from downhole transducers and includes fields labeled Date, Time, LEVEL, and TEMPERATURE.

15 GEOTHERMAL ENERGY↗

ORPC RivGen Hydrokinetic Turbine Wake Characterization

Field measurements of mean flow and turbulence parameters at the Kvichak river prior to and after the deployment of ORPC's RivGen hydrokinetic turbine. Data description and turbine wake analysis are presented in the attached manuscript "Wake measurements from a hydrokinetic river turbine" by Guerra and Thomson (recently submitted to Renewable Energy). There are three data sets: NoTurbine (prior to deployment), Not_Operational_Turbine (turbine underwater, but not operational), and Operational_Turbine. The data has been quality controlled and organized into a three-dimensional grid using a local coordinate system described in the paper. All data sets are in Matlab format (.mat). Variables available in the data sets are: qx: X coordinate matrix (m) qy: Y coordinate matrix (m) z : z coordinate vector (m) lat : grid cell latitude (degrees) lon: grid cell longitude (degrees) U : velocity magnitude (m/s) Ux: x velocity (m/s) Vy: y velocity (m/s) W: vertical velocity (m/s) Pseudo_beam.b_i: pseudo-along beam velocities (i = 1 to 4) (m/s) (structure with raw data within each grid cell) beam5.b5: 5th-beam velocity (m/s) (structure with raw data within each grid cell) tke: turbulent kinetic energy (m2/s2) epsilon: TKE dissipation rate (m2/s3) Reynolds stresses: uu, vv, ww, uw, vw (m2/s2) Variables from the Not Operational Turbine data set are identified with _T Variables from the Operational Turbine data set are identified with _TO

16 TIDAL AND WAVE POWER↗

Advanced Seismic Probabilistic Risk Assessment Methodology: Development of Beta 1.0 MASTODON Toolset

Design of nuclear power plant (NPP) facilities to resist natural hazards has been a part of the regulatory process from the beginning of the NPP industry in the United States, but has evolved substantially over time. The original set of approaches and methods was entirely deterministic in nature and focused on a traditional engineering margins-based approach. However, over time probabilistic and risk-informed approaches were also developed and implemented in US Nuclear Regulatory Commission guidance and regulation. A defense-in-depth framework has also been incorporated into US regulatory guidance over time. As a result, today, the US regulatory framework incorporates deterministic and probabilistic approaches for a range of different applications and for a range of natural hazard considerations. Although the US regulatory framework has continued to evolve over time, the tools, methods and data available to the US nuclear industry to meet the changing requirements have not kept pace. Notably, there is room for improvement in the tools and methods available for external event probabilistic risk assessment (PRA), which is the principal assessment approach used in risk-informed regulations and risk-informed decision-making applied to natural hazard assessment and design. Development of a new set of tools and methods that incorporate current knowledge, modern best practice, and state-of-the-art computational resources would lead to more reliable assessment of facility risk and risk insights (e.g., the plant elements and accident sequences that are most risk-significant), with less uncertainty and reduced conservatisms. Development of the next generation tools and methods for external events PRA is ongoing under the Risk Informed Safety Margins Characterization (RISMC) technical pathway. The RISMC toolkit development centers on integration of the tools and methods under a common framework, MOOSE. These tools and methods make use of existing and newly developed tools and methods, coupled with the experience and data gained in the past decades, to define and analyze more realistic risk assessment models. Specific focus in this report is on the capability to model seismic risk using advanced SPRA methods. Over the last year, significant capability has been added to Mastodon to simulate 3-D wave passage effects through nonlinear soil. Verification has demonstrated the capability of Mastodon to model wave passage effects in 1-D, 2-D, and 3-D. Methods have been developed to incorporate probabilistic floor response capabilities. Additional capability will be added to Mastodon over the next year to implement a robust gapping and sliding element for cyclic shaking, web-based verification and user manuals, stochastic finite elements, and frequency independent damping. Verification of added capabilities has occured in parallel with code writing activities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Potential applications of microbial genomics in nuclear non-proliferation

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as “characteristic communities of microorganisms” found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

59 BASIC BIOLOGICAL SCIENCES↗

ATP3 Unified Field Study Data

ATP3 Unified Field Study DataThe Algae Testbed Public-Private Partnership ATP3 was established with the goal of investigating open pond algae cultivation across different geographic climatic seasonal and operational conditions while setting the benchmark for quality data collection analysis and dissemination. Identical algae cultivation systems and data analysis methodologies were established at testbed sites across the continental United States and Hawaii. Within this framework the Unified Field Studies UFS were designed to characterize the cultivation of different algal strains during all 4 seasons across this testbed network. The dataset presented here is the complete curated climatic cultivation harvest and biomass composition data for each season at each site. These data enable others to do in-depth cultivation harvest techno-economic life cycle resource and predictive growth modeling analysis as well as develop crop protection strategies for the nascent algae industry.NREL Sub award Number DE-AC36-08-GO28308

09 BIOMASS FUELS↗

Performability modeling based on real data: A casestudy

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

Hsueh, M. C.↗

Performability modeling based on real data: A case study

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

Hsueh, M. C.↗

Lunar Processing Cabinet 2.0: Retrofitting Gloveboxes into the 21st Century

In 2014, the Apollo 16 Lunar Processing Glovebox (cabinet 38) in the Lunar Curation Laboratory at NASA JSC received an upgrade including new technology interfaces. A Jacobs - Technology Innovation Project provided the primary resources to retrofit this glovebox into the 21st century. NASA Astromaterials Acquisition & Curation Office continues the over 40 year heritage of preserving lunar materials for future scientific studies in state-of-the-art facilities. This enhancement has not only modernized the contamination controls, but provides new innovative tools for processing and characterizing lunar samples as well as supports real-time exchange of sample images and information with the scientific community throughout the world.

Calaway, M. J.↗

Defining Nature and Extent of Contamination for the Waste Management Area C RCRA Corrective Action Process at the Hanford Site in Southeast Washington - 17403

Determination of the nature and extent of contamination is a critical task in any Resource Conservation and Recovery Act of 1976 (RCRA) Facility Investigation. Nature and extent are typically defined through field investigation results. In some cases, however, physical and/or programmatic limitations on field work can impede efforts to define nature and extent based on field work alone. Both physical and programmatic restrictions affected efforts to characterize soil contamination at Waste Management Area C, on the U.S. Department of Energy's Hanford Site. As a result, fate and transport modeling was undertaken to enhance the definition of the nature and extent of soil contamination at Waste Management Area C. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Utah FORGE 3-2535: Joint EM-Seismic-InSAR Imaging of Fracture Properties - Workshop Presentation

This is a presentation on the Joint Electromagnetic/Seismic/InSAR Imaging of Spatial-Temporal Fracture Growth and Estimation of Physical Fracture Properties During EGS Resource Development project by Lawrence Berkeley National Laboratory, presented by Dr. David Alumbaugh, Staff Scientist. The project's objective was to develop a set of technologies and workflow to image induced fracture generation and growth for an Enhanced Geothermal System (EGS). The project anticipates imaging of the fracture generation and growth at FORGE using a combination of passive seismic, active source borehole EM, and INSAR technology. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Earth resources instrumentation for the Space Station Polar Platform

The spacecraft and payloads of the Space Station Polar Platform program are described in a brief overview. Present plans call for one platform in a descending morning-equator-crossing orbit at 824 km and two or three platforms in ascending afternoon-crossing orbits at 542-824 km. The components of the NASA Earth Observing System (EOS) and NOAA payloads are listed in tables and briefly characterized, and data-distribution requirements and the mission development schedule are discussed. A drawing of the platform, a graph showing the spectral coverage of the EOS instruments, and a glossary of acronyms are provided.

Donohoe, Martin J.↗

Stakeholder Analysis Report Subtask 3.3 – CarbonSAFE Illinois East Sub-Basin Topical Report 8

Effective stakeholder engagement has been proven to be a critical component in the success of numerous CCS activities and is essential if the technology is to be widely developed in the future. This report contains a stakeholder assessment and highlights some engagement activities conducted during the CarbonSAFE Illinois East Sub-Basin Prefeasibility study. This report is intended to lay the groundwork and provide recommendations for the Wabash CarbonSAFE Feasibility project, currently underway in conjunction with the Wabash Valley Resources ammonia plant retrofit taking place at the former Terre Haute US DOE integrated gasification combined cycle plant. The analysis sets the stage for identifying and understanding the concerns of key stakeholders, describes actions currently underway, highlights perceptions of potential benefits and risks of project activities, and provides recommendations for short- and long-term forms of engagement. This study used social site characterization methods to better understand local and regional stakeholder positions and needs. The stakeholder engagement strategy will emphasize engagement with stakeholders that enable project development and those that are impacted by the project. The stakeholder analysis process can be broken down into the four basic steps of: identifying, analyzing, mapping, and prioritizing. Various stakeholders were identified by literature search, and additionally by a group of approximately twenty Indiana University SPEA master’s students via a stakeholder workshop. The stakeholder analysis and mapping process is used to help prioritize stakeholder engagement strategies; engagement strategies must be developed with particular stakeholder concerns in mind and messages tailored to those stakeholders’ needs. The stakeholder map with engagement strategy developed for this analysis suggests state government, industry, federal government, and state education are predicted to have the highest interest and influence and should be a priority focus in engagement. Local media, local landowners, local government, and utilities are predicted to have high influence but low interest and may also be a high priority group to engage. Environmental and economic impacts of activities that are considered to be important by stakeholders in the present day (key) or activities that have taken place in the past (legacy) can impact stakeholder perspectives and need to be considered when creating a stakeholder engagement strategy. The issue of environmental clean-up was identified in both the social media analysis and also through USEPA Environmental Justice analysis tools. Thus, it is clear this will be an important factor for consideration in any stakeholder engagement conducted in and around Terre Haute. Furthermore, stakeholder engagement education materials will need to emphasize that carbon dioxide is not a hazardous material, as well as address FAQs regarding CCS. In addition, recommendations for consideration when developing the stakeholder engagement strategy for projects in the Illinois East Sub-Basin in general and related to the Wabash CarbonSAFE project specifically include: drawing clear lines of responsibility between Wabash Valley Resources and ISGS-led Wabash CarbonSAFE that allow the projects to manage integration and messaging; the need for ISGS and other partners to maintain objectivity and remain trusted sources of information; monitoring of social media and continuing to engage with key stakeholder groups; and providing support for key stakeholders to become sources of project information and project champions.

01 COAL, LIGNITE, AND PEAT↗

Quantitative iTRAQ-based secretome analysis reveals species-specific and temporal shifts in carbon utilization strategies among manganese(II)-oxidizing Ascomycete fungi

Fungi generate a wide range of extracellular hydrolytic and oxidative enzymes and reactive metabolites, collectively known as the secretome, that synergistically drive plant litter decomposition in the environment. While secretome studies of model organisms have greatly expanded our knowledge of these enzymes, few have extended secretome characterization to environmental isolates or directly compared temporal patterns of enzyme utilization among diverse species. Thus, the mechanisms of carbon (C) degradation by many ubiquitous soil fungi remain poorly understood. Here we use a combination of iTRAQ proteomics and custom bioinformatic analyses to compare the protein composition of the secretomes of four manganese(II)-oxidizing Ascomycete fungi over a three-week time course. We demonstrate that although the fungi produce a similar suite of extracellular enzymes, they exhibit striking differences in the regulation of these enzymes among species and over time, revealing species-specific and temporal shifts in C utilization strategies as they degrade the same substrate. Specifically, our findings suggest that Paraconiothyrium sporulosum AP3s5-JAC2a and Alternaria alternata SRC1lrK2f employ sequential enzyme secretion patterns concomitant with decreasing resource availability, Stagonospora sp. SRC1lsM3a preferentially degrades proteinaceous substrate before switching to carbohydrates, and Pyrenochaeta sp. DS3sAY3a utilizes primarily peptidases to aggressively attack carbon sources in a concentrated burst. This work highlights the diversity of operative metabolic strategies among cellulose-degrading Ascomycetes and enhances our understanding of their role in C turnover in the environment.

59 BASIC BIOLOGICAL SCIENCES↗

Characterizing Land Surface Change and Levee Stability in the Sacramento-San Joaquin Delta Using UAVSAR Radar Imagery

The Sacramento-San Joaquin Delta is one of the primary water sources for the state of California and represents a complex geographical area comprised of tidal marshland, levee rimmed islands that are used primarily for agriculture, and urban encroachment. Land subsidence has dropped many of the Delta islands 3 to >7 meters below mean sea level and requires nearly 1700 km of levees to maintain the integrity of the islands and flow of water through the Delta. The current average subsidence rates for each island varies, with 1.23 cm/yr on Sherman Island and 2.2 cm/yr for Bacon Island, as determined by ground-based instruments located at isolated points in the Delta. The Delta's status as the most critical water resource for the state, an endangered ecosystem, and an area continuously threatened with levee breakage from hydrostatic pressure and the danger of earthquakes on several major faults in the San Francisco area make it a focus of monitoring efforts by both the state and national government. This activity is now almost entirely done by ground-based efforts, but the benefits of using remote sensing for wide scale spatial coverage and frequent temporal coverage is obvious. The UAVSAR airborne polarimetric and differential interferometric L-band synthetic aperture radar system has been used to collected monthly images of the Sacramento-San Joaquin Delta and much of the adjacent Suisun Marsh since July 2009 to characterize levee stability, image spatially varied subsidence, and assess how well the UAVSAR performs in an area with widespread agriculture production.

geographical area↗

Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model

Objectives: Sepsis affects nearly 1 million people in the United States per year, has a mortality rate of 28–50% and requires more than $20 billion a year in hospital costs. Over a quarter century of research has not yielded a single reliable diagnostic test or a directed therapeutic agent for sepsis. Central to this insufficiency is the fact that sepsis remains a clinical/physiological diagnosis representing a multitude of molecularly heterogeneous pathological trajectories. Advances in computational capabilities offered by High Peformance Computing (HPC) platforms call for an evolution in the investigation of sepsis to attempt to define the boundaries of traditional research (bench, clinical and computational) through the use of computational proxy models. We present a novel investigatory and analytical approach, derived from how HPC resources and simulation are used in the physical sciences, to identify the epistemic boundary con- ditions of the study of clinical sepsis via the use of a proxy agent-based model of systemic inflammation. Design: Current predictive models for sepsis use correlative methods that are limited by patient heterogeneity and data sparseness. We address this issue by using an HPC version of a system-level validated agent-based model of sepsis, the Innate Immune Response ABM (IIRBM), as a proxy system in order to identify boundary conditions for the possible behavioral space for sepsis. We then apply advanced analysis derived from the study of Random Dynamical Systems (RDS) to identify novel means for characterizing system behavior and providing insight into the tractability of traditional investigatory methods. Results: The behavior space of the IIRABM was examined by simulating over 70 million sepsis patients for up to 90 days in a sweep across the following parameters: cardio-respiratory-metabolic resilience; microbial invasiveness; microbial toxigenesis; and degree of nosocomial exposure. In addition to using established methods for describing parameter space, we developed two novel methods for characterizing the behavior of a RDS: Probabilistic Basins of Attraction (PBoA) and Stochastic Trajectory Analysis (STA). Computationally generated behavioral landscapes demonstrated attractor structures around stochastic re- gions of behavior that could be described in a complementary fashion through use of PBoA and STA. The stochasticity of the boundaries of the attractors highlights the challenge for correlative attempts to characterize and classify clinical sepsis. Conclusions: HPC simulations of models like the IIRABM can be used to generate approximations of the behavior space of sepsis to both establish “boundaries of futility” with respect to existing investi- gatory approaches and apply system engineering principles to investigate the general dynamic properties of sepsis to provide a pathway for developing control strategies. Here, the issues that bedevil the study and treatment of sepsis, namely clinical data sparseness and inadequate experimental sampling of system behavior space, are fundamental to nearly all biomedical research, manifesting in the “Crisis of Reproducibility” at all levels. HPC-augmented simulation-based research offers an investigatory strategy more consistent with that seen in the physical sciences (which combine experiment, theory and simulation), and an opportunity to utilize the leading advances in HPC, namely deep machine learning and evolutionary computing, to form the basis of an iterative scientific process to meet the full promise of Precision Medicine (right drug, right patient, right time).

59 BASIC BIOLOGICAL SCIENCES↗