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Results for “Estimated Ultimate Recovery”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Machine-learning predictions of the shale wells’ performance

The ultra-low permeability nature of shale reservoirs leads to an extended linear flow and necessitates horizontal wells with multi-stage engineered fractures to efficiently extract hydrocarbons resources. These artificially-generated and naturally-occurring fractures form complex networks that create complex flow regimes which control oil production. These fractures are neither identical nor equally-spaced, which leads to a production profile with a masked onset of the boundary-dominated flow. The combination of the extended linear flow with the indeterminate onset of the boundary-dominated flow challenges the current deterministic analytic approaches to forecast the estimated ultimate recovery (EUR). In this work, we propose a novel machine-learning approach which overcomes these challenges and provides reliable EUR estimates based on field-wide analyses. We implement a novel unsupervised machine learning (ML) methodology, which allows for automatic identification of the optimal number of features (signals) present in the data based on non-negative matrix/tensor factorization coupled with k-means clustering incorporating regularization and physics constraints. In the presented analyses, the input data to the ML algorithm is the available (public) production history from the field collected at existing unconventional reservoirs. We validate our approach through hindcasting of the production data, where we achieved an excellent agreement. In addition, our approach is able to identify the poorly-performing wells, which could benefit from early refracing. Our approach provides fast and accurate estimations of the well performance without presumptions about the state of the well or the flow regime.

03 NATURAL GAS↗
DOE OSTI2023

Evaluation of the economic implications of varied pressure drawdown strategies generated using a real-time, rapid predictive, multi-fidelity model for unconventional oil and gas wells

Experience has suggested that pressure maintenance in hydraulically fractured reservoirs via lower, more sustained production drawdowns may offer improved cumulative recovery and overall resource extraction efficiency compared to more rapid drawdown approaches aimed at generating high initial production. However, given the inherent variability of oil and natural gas markets, operators pursue production strategies that maximize profitability over resource extraction efficiency. This study focuses on evaluating the implications of contrasting pressure drawdown strategies on the long-term production and resulting economics for a real, producing unconventional gas well in the Marcellus Shale of the Appalachian Basin using a techno-economic analysis approach. Our research combines elements of well-specific horizontal well design, production forecasting, equipment sizing and capital cost estimation, operating cost estimation, and revenue and tax calculations. Gas production forecast outlook scenarios were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning workflow and 2) traditional reservoir simulation. A discounted cash flow model was used to evaluate the resulting economic implications for each drawdown scenario—generating output for exploring the coupled effect of factors like the timing and volume of gas production, prevailing economic and market conditions for natural gas, and overall estimated ultimate recovery on profitability metrics such as internal rate of return and net present value. Results show that there is potential to maximize the cumulative gas produced in the specific case study well by employing a lower pressure drawdown. Conversely, the greatest profitability is achieved using rapid drawdown as signified by a small, specific subset of our outlook scenarios. On an averaging basis, we find that the combinations of highest cumulative producing and most profitable scenarios occur under lower drawdowns with long (>40 years) producing timeframes, but require higher relative gas price and lower discounting considerations. Further, the machine learning predictive outlooking capability proved effective for enabling rapid generation of a multitude of scenario forecasts. As a result, a variety of prominent example cases could be generated to strike the balance of greater productivity and economic return given their associated producing features and economic conditions when compared to similar producing scenarios—critical insight that offers improved decision support for unconventional oil and gas operations.

42 ENGINEERING↗
DOE OSTI2020

Gaining Perspective on Unconventional Well Design Choices through Play-level Application of Machine Learning Modeling

The recent development of unconventional oil and gas (O&G) reservoirs has led to an abundant hydrocarbon supply, both domestically and globally. However, there is a continued push to develop new and innovative approaches to improve exploration and extraction efficiencies and overall well productivity moving forward. Substantial improvements in unconventional O&G development are expected through optimized well completion and stimulation strategies aimed at maximizing well productivity. Optimizing well designs will require tailoring to the distinctive geologic conditions present for any newly placed well. To better evaluate the impact of well design attributes and their associated interactions on productivity in a major unconventional play, multivariate machine learning-based models that use empirical datasets were developed. A gradient boosted regression tree (GBRT) algorithm was applied. GBRT has been narrowly investigated for O&G applications but enables straightforward parametric importance and influence evaluation, as well as assessment of parameter interaction effects. Models were trained on well design and locational parameters that serve as a proxy for variable geologic conditions to estimate two types of productivity indicator response variables strongly correlated to estimated ultimate recovery (EUR). The dataset utilized consists of over 7,000 well observations that cover the majority of the productive region of the Marcellus Shale. Model performance was evaluated and algorithm parameters tuned by analyzing the goodness-of-fit for simulated results against observed data in a cross-validation approach. Models were found capable of 73–79 percent prediction accuracy on held out testing data of gas equivalent production and can be used to inform future well design and placement decisions for increasing EUR per well and improving overall field-level recovery. Study results indicate that Marcellus well performance improves most with upscaling perforated interval lengths and water and proppant volumes per foot; but relative productivity improvements are spatially dependent across the play. Finally, optimal combinations of water and proppant on well performance were found to vary depending on well location, emphasizing the utility of data-driven models capable of broad application across a play of interest for informing tailored well design approaches prior to their field deployment.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

Evaluation of “Tight Oil” Well Performance and Completion Practices in the Powder River Basin - “Time Slice” Analysis

The objective of this paper is to assess how well completion practices and well performance have evolved over time (“time slices”) in the tight sands and shales of the Powder River Basin (PRB). This information can provide a foundation for helping operators define more effective well completion practices and thus optimize well performance in an emerging “tight oil” basin. To start, the authors assembled a “database” containing well completion practices, production data, and geologic information for more than 800 horizontal (Hz) wells targeting three “tight oil” formations -- Turner, Frontier, and Mowry--placed on production in the past dozen years. To control for the impact of geologic and reservoir properties on well performance, the authors defined 12 geologically distinct areas (“partitions”) for the Turner, Frontier, and Mowry Shale in the Powder River Basin (4 partitions in each formation). This paper discusses the methodology for establishing “time slices” for each partition within each of the three “tight oil” formations, including (1) taking out, to the extent practical, the effects of geology by partitioning the three “tight oil” formations based on their geologic parameters; (2) using type curves and estimated ultimate recoveries (EURs) to establish a reliable measure of well performance; and (3) rigorously inspecting the production and well completion data to assure a quality dataset. Partition #2, a high thermal maturity area of the Frontier Sandstone in the western Powder River Basin, helps illustrate the results of the study. Using a dataset of 55 Hz wells, the study found that well performance has steadily improved, with oil EURs increasing from 180 MBbl in 2012-13 to 290 MBbl in 2018-19. Much of this improvement was due to the use of longer Hz laterals, increasing notably from 3,765 ft in 2012-13 to 10,260 ft in 2018-19. More intensive completion practices contributed, as well. For example, the number of frac stages more than doubled, from 17 to 35, and proppant concentrations increased from 1,060 lbs/ft to 1,320 lbs/ft. Finally, the data show diminishing returns to longer laterals and more intensive completion practices. For example, the key performance measure of oil EUR per 1,000 ft of lateral is decreasing. For 2012-13, Hz wells recovered 50 MBbl of oil per 1,000 ft of lateral while the more recent 2018-19 Hz wells only provide 30 MBbl of oil per 1,000 ft of lateral. Considerable insight can be gained by using “time slices” and geologic partitioning to better understand the relationship between changes in well drilling and completion practices and changes in well performance in emerging “tight oil” plays. The results from this study can also serve as a foundation for subsequent, more intense efforts involving data analytics for defining more optimum well completion practices targeting specified geologic settings and formations.

02 PETROLEUM↗
DOE OSTI2023

Evaluating Production Implications of Pressure Maintenance in Unconventional Oil and Gas Wells using a Machine Learning Modeling Approach: Case Study in the Permian Basin

This study implements the proprietary machine learning-based model (model) developed under the 2022 study titled “Evaluating the Impact of Proprietary Oil & Gas Data on Machine Learning Model Performance Using a Quasi-Experimental Analytical Approach” for forecasting unconventional oil and gas production using well data from the Permian Basin. The model, developed using an exclusive dataset that includes time series production data from an operator in the Permian Basin, is designed to jointly predict daily oil, gas, and water production for horizontal wells as a function of bottomhole pressure drawdown, spatial placement across the study domain, and well-completion attributes. In this study, the model was explicitly applied to explore its utility to evaluate the impact of varying drawdown strategies on the production forecast of a well in the Permian Basin dataset. Managing pressure drawdown has been identified as a way to improve estimated ultimate recovery (EUR) from unconventional shale wells due to the stress-dependent nature of fractures in shale reservoirs. Research has shown that applying a lower pressure drawdown helps to maintain the reservoir conductivity, resulting in higher productivity over the life of a well. Historic bottomhole pressure data from the well over time was used as a benchmark from which to set more and less aggressive pressure decline rates as bounding modeling cases. All pressure decline rates/strategies were forecasted over 5 years, and the model was used to generate oil, water, and gas prediction over the same timeframe. This report presents the results from the production forecast and discusses potential operational and economic implications, with contrasting perspectives between well productivity and profitability given typical oil and gas economics and the volatility in the oil and gas market.

02 PETROLEUM↗
NASA NTRS2014

Past Changes in the Vertical Distribution of Ozone Part 1: Measurement Techniques, Uncertainties and Availability

Peak stratospheric chlorofluorocarbon (CFC) and other ozone depleting substance (ODS) concentrations were reached in the mid- to late 1990s. Detection and attribution of the expected recovery of the stratospheric ozone layer in an atmosphere with reduced ODSs as well as efforts to understand the evolution of stratospheric ozone in the presence of increasing greenhouse gases are key current research topics. These require a critical examination of the ozone changes with an accurate knowledge of the spatial (geographical and vertical) and temporal ozone response. For such an examination, it is vital that the quality of the measurements used be as high as possible and measurement uncertainties well quantified. In preparation for the 2014 United Nations Environment Programme (UNEP)/World Meteorological Organization (WMO) Scientific Assessment of Ozone Depletion, the SPARC/IO3C/IGACO-O3/NDACC (SI2N) Initiative was designed to study and document changes in the global ozone profile distribution. This requires assessing long-term ozone profile data sets in regards to measurement stability and uncertainty characteristics. The ultimate goal is to establish suitability for estimating long-term ozone trends to contribute to ozone recovery studies. Some of the data sets have been improved as part of this initiative with updated versions now available. This summary presents an overview of stratospheric ozone profile measurement data sets (ground and satellite based) available for ozone recovery studies. Here we document measurement techniques, spatial and temporal coverage, vertical resolution, native units and measurement uncertainties. In addition, the latest data versions are briefly described (including data version updates as well as detailing multiple retrievals when available for a given satellite instrument). Archive location information for each data set is also given.

stratospheric ozone layer measurement↗
NASA NTRS2008

Robustness Analysis and Reliable Flight Regime Estimation of an Integrated Resilent Control System for a Transport Aircraft

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. As a part of the validation process, this paper describes an analysis method for determining a reliable flight regime in the flight envelope within which an integrated resilent control system can achieve the desired performance of tracking command signals and detecting additive faults in the presence of parameter uncertainty and unmodeled dynamics. To calculate a reliable flight regime, a structured singular value analysis method is applied to analyze the closed-loop system over the entire flight envelope. To use the structured singular value analysis method, a linear fractional transform (LFT) model of a transport aircraft longitudinal dynamics is developed over the flight envelope by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The developed LFT model can capture original nonlinear dynamics over the flight envelope with the ! block which contains key varying parameters: angle of attack and velocity, and real parameter uncertainty: aerodynamic coefficient uncertainty and moment of inertia uncertainty. Using the developed LFT model and a formal robustness analysis method, a reliable flight regime is calculated for a transport aircraft closed-loop system.

Shin, Jong-Yeob↗
DOE OSTI2021

Fire reduces riverine DOC concentration draining a watershed and alters post-fire DOC recovery patterns

Abstract The loading of dissolved organic carbon (DOC) from soils to inland waters and ultimate transport to the ocean is a critical flux pathway in the terrestrial biosphere carbon cycle. Fires can significantly affect this flux through biogeochemical processes related to oxidation and mobilization of DOC in the soil. Therefore, in order to accurately estimate and model terrestrial carbon storage and export to the marine environment, we need to better understand the effects of fire on DOC flux. In this analysis, we compiled available observational data sets from seven watersheds across the conterminous United States generally spanning the years 1999–2019. We used these data sets to examine the effects of fire on riverine DOC concentration draining a watershed to study both the immediate impacts and the post-fire recovery patterns. Our results suggest that these fires result in an immediate decrease in riverine DOC concentration draining the watershed by 26 ± 15%, and the time required for DOC concentrations to recover to pre-fire levels was estimated to be, on average, approximately 9 months. During recovery, DOC concentration was 24 ± 11% lower than the long-term average for the watershed. In addition, the larger the proportion of the watershed that burned, the greater the concentration decrease and the longer the time period for post-fire recovery.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Approaches to resource recovery in controlled ecological life support systems

Recovery of resources from waste streams in a space habitat is essential to minimize the resupply burden and achieve self sufficiency. The ultimate goal of a Controlled Ecological Life Support System (CELSS) is to achieve the greatest practical level of mass recycle and provide self sufficiency and safety for humans. Several mission scenarios leading to the ultimate application could employ CELSS component technologies or subsystems with initial emphasis on recycle of the largest mass components of the waste stream. Candidate physical/chemical and biological processes for resource recovery from liquid and solid waste streams are discussed and the current fundamental recovery potentials are estimated.

Bubenheim, D. L.↗
DOE OSTI2022

Using Natural Gas Liquids to Recover Unconventional Oil and Gas Resources (Final Report)

This document presents final technical findings for the project Using Natural Gas Liquids to Recover Unconventional Oil and Gas Resources (FE0031782). The project is part of the U.S. Department of Energy Oil and Gas Program to develop and advance technologies that can significantly improve the recovery efficiencies of unconventional oil and gas resources. The overall objective of this project is to improve the ultimate recovery from unconventional oil and gas (UOG) resources in the United States by developing a method for using unrefined natural gas liquids (NGLs) as treatment fluids to improve hydrocarbon production. Horizontal extended-lateral drilling coupled with high volume hydraulic fracturing has significantly increased production from UOG resources in the U.S. However, the recovery efficiency is low compared to the estimated oil and gas in place. Recent data indicate that less than 10% of the oil in the liquid-rich UOG reservoirs is produced. Alternative completion methods using NGLs could increase production (Battelle, 2016; Wan et al., 2013; Wan, 2013; Downey et al, 2021); however, field validation tests are needed to develop an approach that is economical, efficient, and compatible in the UOG setting to advance towards commercial deployment. This project aims to develop and field test a method to improve recovery of oil resources in UOG shale plays by using Y-Grade NGLs, or a similar combination of NGLs, as treatment fluids. Refined NGLs have been used as a hydraulic treatment fluid in UOG plays for decades and are shown to be particularly effective because their miscibility with oil allows oil to flow more freely; however, the use of Y-Grade (unrefined) NGLs has not been studied. The use of Y-Grade NGLs would be advantageous over refined NGLs because Y-Grade NGLs do not require infrastructure or investment in refining and are already being produced from many UOG reservoirs. The concept was tested and monitored in the field at a commercial well site owned by project partner Hopco, Ltd. The project team, which consists of multiple oil and gas operators, Linde Gas North America LLC (Linde) and the Ohio Division of Geological Survey (ODGS), has extensive experience with oil and gas production in the Appalachian basin and the ability to work together quickly to solve technical issues and research needs. A key part of the proposed work was the use of existing wells for field testing and monitoring. A total of four wells (three vertical and one horizontal) were available for this project. One of the vertical wells was utilized as the test well for the NGL treatment test. A nearby vertical well was used for microseismic monitoring. The remaining vertical well and the horizontal well provided a baseline for typical UOG production in the oil window of the Utica/Point Pleasant (UPP). Major technical tasks of the project include characterization of the geotechnical properties of the UPP with an emphasis on the field site; design and planning for the NGLs testing; field testing and monitoring; analysis and integration of field data; and economic and resource/reserve assessment. The Shoman monitoring well and Doughty NGL treatment well were successfully plugged back during September-October 2020 in preparation for treatment and monitoring. A nitrogen diagnostic fracture injection test (DFIT) was completed on the Doughty well on July 22, 2021, consisting of 133,000 scf (91 Bbl.) of nitrogen. A nitrogen foam frac was completed in the Utica-Point Pleasant interval on August 17, 2021 with funding from outside sources. A microseismic monitoring array was installed in the Shoman well and monitored microseismic activity during the Doughty well frac job. Y-Grade NGL injection commenced on August 26, 2021. A total of 215 Bbl. was injected but the job was shut down due to a small leak on the suction hose on the pump truck. The Y-Grade treatment resumed on August 27, 2021 and an additional 726 Bbl. of Y-Grade NGL was injected at a well head pressure of 3850 psi. Total volume of injected Y-Grade over the two days of injection was 941 Bbl. The well was shut-in for 17 days following injection to allow the Y-Grade NGLs to soak on the formation. Y-Grade treatment flow back commenced on 9/13/2021 on a weekly basis. Production data, including surface pressures, oil, nitrogen, natural gas, and flow times was measured and recorded. Periodic gas samples were collected and analyzed to determine composition of flowback gas. As of July 2022, the treatment well had produced 726 Bbl of oil and 2,888 mcf gas. In August 2022, tubing and packer in the well were removed and a pump was installed to enhance oil recovery. Currently, the operator is producing the well about 2 days a week for a few hours. The performance of the NGL treatment test was evaluated based on reservoir simulations of the treatment process, processing of well testing data, analysis of micro seismic monitoring data, and production data analysis. This analysis suggested that oil production in the small test would continue through 2025. Upscaling the treatment to a horizontal Utica Point-Pleasant well would allow more oil recovery, but the process would involve more investment, services, and operational support. An economic analysis was conducted for scenarios aimed at upscaling the NGL treatment process for more typical horizontal UPP wells in the Appalachian Basin.

02 PETROLEUM↗
DOE OSTI2022

Preprocessing of municipal solid waste towards thermal insulating material

Municipal solid waste (MSW) is one of the significant challenges in today’s world. A continuous surge in population, increasing living standards, and rapid urbanization are generating an enormous quantity of MSW. For example, the Environmental Protection Agency (EPA) reported that the total generation of MSW in the United States in 2018 was 292.4 million tons. Improper management of this MSW often leads to the release of greenhouse gases, emission of particulate matters, and formation of dioxins, which all ultimately contributes to climate change. Recycling these wastes via landfills with gas recovery and/or energy and material production via thermal and chemical conversions could be viable options to manage these challenges. Depending on the inherent chemical and structural properties of unrecycled wastes, the carbon structures can be tailored for processing and reuse in manufacturing of structural composites, building materials such as insulation, carbon dense reactant materials such as activated carbon, and so on. According to the EPA’s estimation, MSW in the United States is approximately 23% paper and paperboard, 12% plastics, 6% wood and 6% is textiles. Thus, this research focused on the feasibility of using the MSW as insulation material for the construction sector. The goal of this work was to determine the range of particle sizes, consolidation ratios, and component blends that can achieve insulation R-values within at least 70% that of traditional blown cellulose fiber. To achieve this goal, we designed the testing matrix based on five different component blends, three different particle sizes, and three different compaction level. An American Society for Testing and Materials (ASTM) method (C-739) was used to measure the R-value of the insulation material. Results showed that, adding more paper component in addition to smaller particle size and loose compaction made the insulation similar to the traditional blown cellulose fiber insulation as the R-value was within a range of 2.5-3.0 per inch.

42 ENGINEERING↗
NASA NTRSDate not supplied

Modeling Uprighting of the Orion Crew Module using a Finite Element Method with Wave Coupling and Structural Deformability

The Crew Module Uprighting System (CMUS) for the Orion Crew Module (CM) includes five bags that inflate after splashdown to rotate and upright the CM as necessary. Wave conditions can be severe enough to damage the bags and tethers, which could make the recovery operation hazardous. The CMUS therefore has design limits that ultimately constrain where the CM can land based upon sea conditions. This manuscript describes a full fluid-structure interaction computational model being used for the CMUS. It is a finite element model that uses explicit time integration to directly simulate uprighting, a computational approach usually reserved for short duration, highly transient phenomena and novelly applied here. The goal of this current effort is to determine the feasibility of this approach for CMUS uprighting, and to estimate the loads the CMUS bags experience in different wave conditions. The results from this work will be used to supplement other experimental and computational data in support of NASA’s Artemis program.

John Puryear↗
DOE OSTI2024

Investigating Material Properties of Subsurface Rock Formations Modified by Engineering Mineral Precipitation (Final Scientific and Technical Report)

Montana State University’s (MSU) Energy Research Institute (ERI), in collaboration with the Center for Biofilm Engineering (CBE) and the Department of Civil Engineering (CE), has conducted a long‐term research program aimed at developing a novel cementing agent to address wellbore integrity and reduce the unwanted upward migration of fluids and greenhouse gases from the subsurface. The primary technology developed through this research program is known as ureolysis‐induced calcite precipitation (UICP), which harnesses bio‐chemical processes to precipitate calcium carbonate (CaCO 3 ). The same general process can also be called microbially-induced calcium carbonate precipitation (MICP) when microbes provide the process-catalyzing urease enzyme. Both terms are used in this report. Results have conclusively demonstrated that, if properly controlled, UICP can successfully seal fractures, high permeability zones, and compromised cement in the vicinity of wellbores and in nearby caprock. This technology has been successfully deployed to mitigate annular leakage in two test wells and over sixty commercial wells with a 100% success rate. This success in downhole deployment generates consideration of other subsurface applications where UICP could provide benefit to the energy sector, such as shale property modification for unconventional oil and gas recovery. The focus of this research project was to investigate fundamental material and mechanical properties of select shale cores and analyze how these properties change due to engineered mineral precipitation with the intent to control these properties to achieve a range of engineering objectives. Ultimately, the project aim was to identify valuable new areas where application of UICP might contribute to national energy security and environmental protection. The research workplan coupled UICP treatment of core samples, nuclear magnetic resonance (NMR) characterization, and mechanical strength testing at MSU with advanced X‐Ray micro-computed tomography (μCT) imaging and numerical modeling performed by collaborators at two national laboratories, the National Energy Technology Laboratory (NETL) and Lawrence Berkeley National Laboratory (LBNL). Experimental results are useful to inform geo-mechanical models which could be applied to predict mineralized rock formation behavior at field scale. Our findings suggest that NMR and μCT methods to detect and quantify biomineral formation in shale fractures are complementary and consistent with each other. Either could be used to estimate the volume of new mineral formed by UICP in shale fractures. The use of surfactants and guar gum to enhance biomineral precipitation in shale fractures merits further research. UICP can, under some conditions, increase the tensile strength of sealed shale fractures beyond that of the intact shale. These findings demonstrate that continued research in this area may be valuable to understanding and improving shale resource recovery techniques.

58 GEOSCIENCES↗
DOE OSTI2020

Modeling the Functional Forms of Grid Disturbances

This report introduces a functional form that may be used to quantitatively predict the impacts of new grid tools and changing system qualities on the likelihoods, durations, and depths of various grid disturbances. Each disturbance scenario is modeled to have three component stages—avoidance, reactance and recovery, which together parametrically estimate one disturbance’s impacts. The modeled scenario is then placed and replicated within an analysis period to represent the likelihood or frequency of the scenario and its consequent impacts. Whereas analysts have struggled to define and apply metrics for grid resilience, the functional form introduced by this report shares units of measurement with accepted grid-status measures (e.g., numbers of customers currently experiencing a service outage). Furthermore, the integrated and averaged functional form over an analysis period provides a meaningful normalized performance metric (e.g., customer outage minutes per year) that is ultimately independent of the duration of the period of. The approach may be applied similarly regardless of the severity or frequency of the disturbances that are being analyzed. Because metrics can be chosen to be identical in both the hypothetical future and the actual historical past, the historical past eventually becomes the test of the future predictions, at least in a statistical sense. The authors originally developed this approach to facilitate analysis of the effects of transactive energy (TE) systems effects on electric power grid resilience. TE systems invite energy suppliers and consumers to actively collaborate toward the discovery of, and their responses to, the locational value of energy. The findings from this process are often embodied as energy prices, the dynamics of which indicate the locational value of energy and can further represent important grid service needs. While some academic papers claim to quantify the value of a specific TE system design toward grid resilience, the answer, in general, has been elusive. Not only do multiple and conflicting definitions of resilience and reliability exist, but countless TE systems are being invented. We conclude the following: (1) The ideal analysis should harmonize rather than differentiate resilience and reliability. Therefore, this report uses the more general term disturbance whenever the overloaded terms resilience and reliability can be avoided. (2) The effectiveness of TE systems must be mapped to underlying qualities of a TE system, thereby avoiding presumptions that every TE design offers similar advantages. The authors seek to evaluate the parametric effects of TE system qualities (e.g., spatial granularity, granularity of time steps, length of future prediction horizon) on avoiding, reacting to, and recovering from grid disturbances. Furthermore, any advantages (or disadvantages) must be fairly compared with the many alternative tools, systems, and strategies that might offer comparable benefits.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2021

Estimating Terrestrial Snow Mass via Multi-sensor Assimilation of Synthetic AMSR-E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals

This study explores multi-sensor data assimilation (DA) using synthetic Advanced Microwave Scanning Radiometer (AMSR-E) passive microwave brightness temperature spectral differences (∆T(B)) and synthetic Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) retrievals to improve estimates of snow water equivalent (SWE), subsurface water storage, and TWS across snow-covered terrain. Results show that multi-sensor DA improves SWE estimates by reducing the RMSE by 14.1% relative to a model-only simulation. Multi-sensor assimilation also yields the smallest TWS RMSE (reduced by 13.0% relative to a model-only simulation). However, multi-sensor DA does not always yield complementary updates, and can sometimes lead to conflicting changes to SWE, where the assimilation of synthetic ∆T(b) generates positive SWE increments while the assimilation of synthetic TWS removes SWE, which can ultimately degrade the posterior SWE estimates. This synthetic experiment provides useful insight for future DA experiments using real-world AMSR-E/AMSR-2 ∆T(b) observations and GRACE/GRACE-FO TWS retrievals to better characterize terrestrial freshwater storage across regional scales.

Jing Wang↗
DOE OSTI2020

A Dynamic Trajectory Fit to Multisensor Fireball Observations

Meteorites with known orbital origins are key to our understanding of solar system formation and the source of life on Earth. Fireball networks have been developed globally in a unified effort to record and ultimately retrieve these cosmic samples. However, the accuracy of the determined orbit and the likelihood of meteorite recovery depend directly on the accuracy of the chosen meteoroid triangulation method. There are three leading techniques for meteoroid triangulation discussed in the literature: the method of planes, the straight-line least-squares method, and the multiparameter fit method. Here we describe an alternative method to meteoroid triangulation, called the dynamic trajectory fit. This approach uses the meteoroid’s 3D dynamic equations of motion to fit a realistic trajectory directly to multisensor line-of-sight observations. This method has the ability to resolve fragmentation events, fit systematic observatory timing offsets, and determine mass estimates of the meteoroid along its observable trajectory. Through a comprehensive Monte Carlo analysis of over 100,000 trajectory simulations, we find this new method to more accurately estimate meteoroid trajectories of slow entry events (<25 km s{sup −1}) and events observed from low convergence angles (<10°) compared to existing meteoroid triangulation techniques. Additionally, we triangulate an observed fireball event with visible fragmentation using the various triangulation methods to show that the proposed dynamic trajectory fit implementing fragmentation to best match the captured multisensor line-of-sight data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

Failure Analysis Results and Corrective Actions Implemented for the Extravehicular Mobility Unit 3011 Water in the Helmet Mishap

Water entered the Extravehicular Mobility Unit (EMU) helmet during extravehicular activity (EVA) no. 23 aboard the International Space Station on July 16, 2013, resulting in the termination of the EVA approximately 1 hour after it began. It was estimated that 1.5 liters of water had migrated up the ventilation loop into the helmet, adversely impacting the astronaut's hearing, vision, and verbal communication. Subsequent on-board testing and ground-based test, tear-down, and evaluation of the affected EMU hardware components determined that the proximate cause of the mishap was blockage of all water separator drum holes with a mixture of silica and silicates. The blockages caused a failure of the water separator degassing function, which resulted in EMU cooling water spilling into the ventilation loop, migrating around the circulating fan, and ultimately pushing into the helmet. The root cause of the failure was determined to be ground-processing shortcomings of the Airlock Cooling Loop Recovery (ALCLR) Ion Filter Beds, which led to various levels of contaminants being introduced into the filters before they left the ground. Those contaminants were thereafter introduced into the EMU hardware on-orbit during ALCLR scrubbing operations. This paper summarizes the failure analysis results along with identified process, hardware, and operational corrective actions that were implemented as a result of findings from this investigation.

Steele, John↗
NASA NTRS2004

Minimizing Launch Mass for ISRU Processes

The University of Dayton and the Jet Propulsion Laboratory are developing a methodology for estimating the Earth launch mass (ELM) of processes for In-Situ Resource Utilization (ISRU) with a focus on lunar resource recovery. ISRU may be enabling for both an extended presence on the Moon, and for large sample return missions and for a human presence on Mars. To accomplish these exploration goals, the resources recovered by ISRU must offset the ELM for the recovery process. An appropriate figure of merit is the cost of the exploration mission, which is closely related to ELM. For a given production rate and resource concentration, the lowest ELM - and the best ISRU process - is achieved by minimizing capital equipment for both the ISRU process and energy production. ISRU processes incur Carnot limitations and second law losses (irreversibilities) that ultimately determine production rate, material utilization and energy efficiencies. Heat transfer, chemical reaction, and mechanical operations affect the ELM in ways that are best understood by examining the process's detailed energetics. Schemes for chemical and thermal processing that do not incorporate an understanding of second law losses will be incompletely understood. Our team is developing a methodology that will aid design and selection of ISRU processes by identifying the impact of thermodynamic losses on ELM. The methodology includes mechanical, thermal and chemical operations, and, when completed, will provide a procedure and rationale for optimizing their design and minimizing their cost. The technique for optimizing ISRU with respect to ELM draws from work of England and Funk that relates the cost of endothermic processes to their second law efficiencies. Our team joins their approach for recovering resources by chemical processing with analysis of thermal and mechanical operations in space. Commercial firms provide cost inputs for ELM and planetary landing. Additional information is included in the original extended abstract.

England, C.↗