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

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Numerical Modeling of CO2 Sequestration within a Five-Spot Well Pattern in the Morrow B Sandstone of the Farnsworth Hydrocarbon Field: Comparison of the TOUGHREACT, STOMP-EOR, and GEM Simulators

The objectives of this study were (1) to assess the fate and impact of CO2 injected into the Morrow B Sandstone in the Farnsworth Unit (FWU) through numerical non-isothermal reactive transport modeling, and (2) to compare the performance of three major reactive solute transport simulators, TOUGHREACT, STOMP-EOR, and GEM, under the same input conditions. The models were based on a quarter of a five-spot well pattern where CO2 was injected on a water-alternating-gas schedule for the first 25 years of the 1000 year simulation. The reservoir pore fluid consisted of water with or without petroleum. The results of the models have numerous broad similarities, such as the pattern of reservoir cooling caused by the injected fluids, a large initial pH drop followed by gradual pH neutralization, the long-term persistence of an immiscible CO2 gas phase, the continuous dissolution of calcite, very small decreases in porosity, and the increasing importance over time of carbonate mineral CO2 sequestration. The models differed in their predicted fluid pressure evolutions; amounts of mineral precipitation and dissolution; and distribution of CO2 among immiscible gas, petroleum, formation water, and carbonate minerals. The results of the study show the usefulness of numerical simulations in identifying broad patterns of behavior associated with CO2 injection, but also point to significant uncertainties in the numerical values of many model output parameters.

STOMP↗
DOE OSTI2020

Numerical study of the effect of propped surface area and fracture conductivity on shale gas production: Application for multi-size proppant pumping schedule design

Hydraulic fracturing is a technique extensively used in the oil and gas industry, where water, proppant (sand) and additives are injected into unconventional reservoirs to enhance the recovery of shale hydrocarbon. Although some previous studies have developed pumping schedules that maximize gas production for a single-size proppant, there are very few studies that consider the effect of varying proppant diameters across pumping stages on shale gas production. Motivated by this, we carried out an extensive sensitivity analysis to determine the effect of different proppant diameters on the average fracture conductivity (FC), average propped surface area (PSA) and cumulative shale gas production volume. We found out that the cumulative shale gas production volume depends on both the average PSA and average FC. We also found out that small-diameter proppant resulted in higher average PSA and lower average FC, whereas large-diameter proppant resulted in lower average PSA and higher average FC. Hence, we designed a multi-size proppant pumping schedule considering both of these parameters into account for simultaneously propagating multiple fractures to maximize shale gas production from unconventional reservoirs. Since the size of injected proppant particles determines the average PSA and average FC for the propped hydraulic fractures, we developed a novel framework called Sequentially Interlinked Modeling Structure (SIMS) to predict the average PSA, average FC and cumulative shale gas production volume at the end of 10 years for a given pumping schedule. Then, we used this SIMS framework to obtain a multi-size proppant pumping schedule that maximizes shale gas production. In closing, we demonstrated that the obtained pumping schedule gives a cumulative shale gas production volume greater than the values obtained from the existing pumping schedules.

03 NATURAL GAS↗
NASA NTRS1998

Lunar prospector mission design and trajectory support

The Lunar Prospector mission is the first dedicated NASA lunar mapping mission since the Apollo Orbiter program which was flown over 25 years ago. Competitively selected under the NASA Discovery Program, Lunar Prospector was launched on January 7, 1998 on the new Lockheed Martin Athena 2 launch vehicle. The mission design of Lunar Prospector is characterized by a direct minimum energy transfer trajectory to the moon with three scheduled orbit correction maneuvers to remove launch and cislunar injection errors prior to lunar insertion. At lunar encounter, a series of three lunar orbit insertion maneuvers and a small circularization burn were executed to achieve a 100 km altitude polar mapping orbit. This paper will present the design of the Lunar Prospector transfer, lunar insertion and mapping orbits, including maneuver and orbit determination strategies in the context of mission goals and constraints. Contingency plans for handling transfer orbit injection and lunar orbit insertion anomalies are also summarized. Actual flight operations results are discussed and compared to pre-launch support analysis.

Lozier, David↗
NASA NTRS2016

Enabling International Data Relay at Mars

The most commonly used mode of communications be-tween Earth and a Mars surface mission is ultra-high fre-quency (UHF) radio relay via a Mars orbiter. There are four orbiters and two surface rovers operating at Mars and by October there should be five orbiters and three landers or rovers. There has been some collaboration between ESA’s Mars Express orbiter and NASA’s rovers, but 2016 is when Mars relay becomes fully international. In October, ESA will deliver the ExoMars Trace Gas Orbiter (TGO) and En-try, Descent, and Landing (EDL) Demonstrator Module (EDM) lander to Mars. The ExoMars program includes both ESA and ROSCOSMOS, with NASA participation (the Electra UHF transceiver on TGO). NASA orbiters will pro-vide relay for EDM and future ESA Mars landers and rov-ers. TGO will provide relay for NASA's current and future surface assets (as Mars Express will continue to do). Inter-national collaboration is enabled in several steps. At the in-struction of the space agencies, the Mars mission projects negotiate and write a “Service Agreement.” This describes at a high level how a new Mars orbiter would operate with its corresponding surface missions or how a new surface mis-sion would operate with its corresponding orbiters. It in-cludes the roles of the different projects, how the new mis-sion would communicate with existing or planned missions, the general flow of data and commands, and the capabilities or requirements of the new mission. After completing the Service Agreement, the projects write Interface Control Doc-uments (ICDs), each of which describes data and command flow in greater detail and quantitative aspects of the relay link and operations timeline between an orbiter and a cor-responding lander/rover. Interfaces and operations are test-ed before a new mission arrives at Mars. Once at Mars, a new orbiter performs some “practice” relay contacts with its partners. For a new lander (e.g. EDM), relay operations gen-erally begin before atmospheric entry at Mars, with record-ing of the UHF relay signal from the lander (including open-loop wide-bandwidth recording) as it enters and traverses Mars’s atmosphere and lands on its surface. After Mars EDL or orbit injection, each relay contact is negotiat-ed and scheduled using the Mars Relay Operations Service (MaROS). This paper describes the international approach to develop inter-agency agreements, inter-project interfaces, and specifics of how MaROS is used in actual relay opera-tions between international partners.

Winton, Alistair J.↗
NASA NTRS1993

A comparison of multiprocessor scheduling methods for iterative data flow architectures

A comparative study is made between the Algorithm to Architecture Mapping Model (ATAMM) and three other related multiprocessing models from the published literature. The primary focus of all four models is the non-preemptive scheduling of large-grain iterative data flow graphs as required in real-time systems, control applications, signal processing, and pipelined computations. Important characteristics of the models such as injection control, dynamic assignment, multiple node instantiations, static optimum unfolding, range-chart guided scheduling, and mathematical optimization are identified. The models from the literature are compared with the ATAMM for performance, scheduling methods, memory requirements, and complexity of scheduling and design procedures.

Storch, Matthew↗
NASA NTRSDate not supplied

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗
NASA NTRSDate not supplied

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗
NASA NTRS2024

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗
DOE OSTI2021

In silico trials predict that combination strategies for enhancing vesicular stomatitis oncolytic virus are determined by tumor aggressivity

Background Immunotherapies, driven by immune-mediated antitumorigenicity, offer the potential for significant improvements to the treatment of multiple cancer types. Identifying therapeutic strategies that bolster antitumor immunity while limiting immune suppression is critical to selecting treatment combinations and schedules that offer durable therapeutic benefits. Combination oncolytic virus (OV) therapy, wherein complementary OVs are administered in succession, offer such promise, yet their translation from preclinical studies to clinical implementation is a major challenge. Overcoming this obstacle requires answering fundamental questions about how to effectively design and tailor schedules to provide the most benefit to patients. Methods We developed a computational biology model of combined oncolytic vaccinia (an enhancer virus) and vesicular stomatitis virus (VSV) calibrated to and validated against multiple data sources. We then optimized protocols in a cohort of heterogeneous virtual individuals by leveraging this model and our previously established in silico clinical trial platform. Results Enhancer multiplicity was shown to have little to no impact on the average response to therapy. However, the duration of the VSV injection lag was found to be determinant for survival outcomes. Importantly, through treatment individualization, we found that optimal combination schedules are closely linked to tumor aggressivity. We predicted that patients with aggressively growing tumors required a single enhancer followed by a VSV injection 1 day later, whereas a small subset of patients with the slowest growing tumors needed multiple enhancers followed by a longer VSV delay of 15 days, suggesting that intrinsic tumor growth rates could inform the segregation of patients into clinical trials and ultimately determine patient survival. These results were validated in entirely new cohorts of virtual individuals with aggressive or non-aggressive subtypes. Conclusions Based on our results, improved therapeutic schedules for combinations with enhancer OVs can be studied and implemented. Our results further underline the impact of interdisciplinary approaches to preclinical planning and the importance of computational approaches to drug discovery and development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Monitoring of corrosion effects in pipes with multi-mode acoustic signals

Current commercial long-range guided wave inspection and monitoring technologies for pipes usually require establishment of certain specific acoustic modes for wave propagation and use a large number of sensors in a certain geometric arrangement (for example, uniformly-spaced arrays of sensors on a collar, placed around a pipe). This paper, in contrast, presents a long-range corrosion detection method in pipes based on multi-mode guided acoustic waves, generated and received using simple, single-element sensors. In this technique, available guided wave modes in any interrogated zone of the structure are automatically down-selected by the medium, and changes in energy distribution over the selected modes are analyzed through signal processing to monitor material loss or addition. Here, to investigate the feasibility of the proposed method, we have performed both experimental and numerical simulation studies on 50.8-mm (2-in)-diameter schedule-40 carbon steel pipes. In these studies, a linear chirp signal is injected in compression mode, perpendicular to the surface of the pipe, generating multi-mode, multi-directional guided waves that travel within the pipe wall. Corrosion effects in the pipes are simulated numerically and experimentally. To reduce errors in the measurement technique due to changes in the local or global temperature of the measured media, a universal temperature compensation algorithm is introduced. The experimental results show good agreement with simulation results, indicating that the proposed multi-mode wave generation and detection in a pipe could be used for long-range detection and monitoring of corrosion effects, such as pipe wall losses or solid material deposits.

36 MATERIALS SCIENCE↗
NASA NTRS2007

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Mizell, Carolyn Barrett↗
DOE OSTI2023

Thermo-Hydrological Modeling of Thermal Energy Storage in a Depleted Oil Reservoir

Thermal energy storage in oil and gas reservoirs leverages the existing surface and subsurface infrastructure, which can pave the way for economic production of geothermal energy. Existing studies on geothermal energy storage are focused mostly on the use of aquifers with more homogeneous rock and fluid properties. Coupling of heat and fluid flow in a multiphase-multicomponent system, such as an oil reservoir, is imperative especially if existing oil field assets need to be repurposed as required for a sustainable energy transition. The objective is to model the subsurface thermo-hydrological processes associated with reservoir performance and operational sustainability. The model evaluates formation pressure and temperature within the reservoir and at the injection/production wells during multiple charge and discharge cycles. Hot water (approximately 200 degrees C) heated by Concentrating Solar Power (CSP) at high pressure is injected into the existing oil reservoir for storage and produced as thermal energy for power generation, which will be accompanied by enhanced oil recovery. To demonstrate the coupled fluid and heat flow during the injection/production cycle in the subsurface reservoir, TOUGH3 (developed by Berkeley Lab) is used to simulate the thermo-hydrological (TH) processes in a multiphase, multicomponent system. Two well geometries are considered within the reservoir grid: 1) a single-well huff-n-puff system (same well is used for injection and production), and 2) an isolated injection-production well doublet. Seasonal charge and discharge cycling are implemented based on the scheduling specified in the model input file. The model reports pressure, temperature, enthalpy, liquid fluxes, heat fluxes, pore velocities, and changes in porosity & permeability due to temperature and pressure variations during the cyclic Reservoir Thermal Energy Storage (RTES) operations. The results from the simulations can be used to optimize the operational parameters (such as well spacing and injection/production rates) and round-trip efficiency for surface power-plants coupled with thermal energy storage over time. They can also serve as important inputs for levelized cost of storage estimations. The research will help to design and integrate surface renewable energy sources, such as concentrating solar power (CSP), with RTES to help balance out power supply and demand on the grid.

CSP↗
NASA NTRS1975

Inlet performance of the integrated Langley scramjet module

The inlet concept for the Langley Scramjet Module has been developed and proven in Langley wind tunnels over a Mach number range from 2.3 to 6.0 (flight simulation of Mach 2.6 to 7.6). This modular engine concept is designed to integrate with the airframe, which results in precompression of the engine airflow by the vehicle bow shock and additional expansion of the nozzle exhaust gas by the afterbody of the vehicle. With these integration advantages, the inlet can be designed with modest contraction ratios and fixed geometry. Also, the module nozzle exit area can be equal to the capture area, which permits the cowl to be alined with the local flow producing minimum external drag. The inlet leading edges and planar compression surfaces are swept at 48 deg, which provides spillage at low Mach numbers for starting and which reduces the pressure gradient on the top surface to permit ingestion of the vehicle forebody boundary layer into the inlet without separating. Three fuel injection struts provide for the use of a short combustor having low internal cooling requirements. Schedules for mass capture ratio, contraction ratio, and total pressure recovery are well within the acceptable range for a good scramjet propulsion device. The fixed geometry, minimum external drag design has proven to be a practical, high-performance inlet concept.

Trexler, C. A.↗
NASA NTRS1976

Teledyne Continental Motors emissions data and analysis and flight test results

Five different engine models were tested covering combinations of all engine categories in current production in the range from 100 to 435 brake horsepower. Engines were divided into five major types: carbureted, fuel injected, direct drive, geared, and turbocharged. Emissions data were categorized by three separate fuel system schedules: baseline, case 1, and case 2. Baseline was defined as the average fuel flow rate established by the fuel system's production tolerance band when operated with the mixture control at the full-rich position. Case 1 was defined as the minimum allowable fuel flow rate established by the engine certification. Case 2 was defined as the fuel rate corresponding to the leanest fuel-air ratio obtainable before a safety limit occurred with the engine operating on a propeller test stand. Safety limits that developed during testing were cylinder-head overheating or inadequate acceleration from a given mode of operation.

Rezy, B. J.↗
NASA NTRS1971

Optimal N-burn multiorbit injection

Procedure for computing gravity losses over n-burn multiorbit escape trajectories of specified final energy and prediction of optimal burn schedules for nuclear rocket escape maneuvers

Singleton, R. L., Jr.↗
DOE OSTI2020

Model predictive control for voltage restoration in microgrids using temporal logic specifications

Power system operation will encounter numerous voltage variabilities as the proliferation of renewable energy continues. Real-time monitoring and communication technologies can potentially improve voltage stability by enabling the rapid detection of voltage deviations and the implementation of corrective actions. These corrective actions will only be effective in restoring stability if they are chosen in a timely and scalable manner. This paper considers the problem of power systems’ load voltage control in order to simultaneously address both magnitude and time voltage specifications. In order to comply with grid codes and avoid unnecessary relay protection actions, a model predictive control (MPC)-based control strategy employing temporal logic specifications (TLSs) is proposed. The TLSs strategy is introduced as a formalism to control the voltage variation at a critical load bus against operational bounds over time. The control objective is to schedule optimal control input signals from the available supportive energy storage systems, which provide reactive power injections, leading to satisfying the specified finite-time restoration described by the TLSs with minimal control efforts. The simulation results display that the TLSs strategy for power systems’ voltage control synthesis is extremely significant.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1999

Five-Hole Flow Angle Probe Calibration for the NASA Glenn Icing Research Tunnel

A spring 1997 test section calibration program is scheduled for the NASA Glenn Research Center Icing Research Tunnel following the installation of new water injecting spray bars. A set of new five-hole flow angle pressure probes was fabricated to properly calibrate the test section for total pressure, static pressure, and flow angle. The probes have nine pressure ports: five total pressure ports on a hemispherical head and four static pressure ports located 14.7 diameters downstream of the head. The probes were calibrated in the NASA Glenn 3.5-in.-diameter free-jet calibration facility. After completing calibration data acquisition for two probes, two data prediction models were evaluated. Prediction errors from a linear discrete model proved to be no worse than those from a full third-order multiple regression model. The linear discrete model only required calibration data acquisition according to an abridged test matrix, thus saving considerable time and financial resources over the multiple regression model that required calibration data acquisition according to a more extensive test matrix. Uncertainties in calibration coefficients and predicted values of flow angle, total pressure, static pressure. Mach number. and velocity were examined. These uncertainties consider the instrumentation that will be available in the Icing Research Tunnel for future test section calibration testing.

Gonsalez, Jose C.↗
NASA NTRS1962

Application of Statistical Filter Theory to the Optimal Estimation of Position and Velocity on Board a Circumlunar Vehicle

Concepts from statistical filter theory are applied to the problem of in-flight determination of the position and velocity of a space vehicle for the purposes of midcourse guidance. The source of information is assumed to be an arbitrary sequence of measurements of any desired set of "observables" (e.g., space angles), the measurements being corrupted by additive errors so that the position and velocity are never known perfectly. A state transition approach is employed which leads naturally to a computational scheme that is readily implemented by a digital computer. The scheme can be regarded as a dynamical time-varying filter which weights the incoming observations in an optimal sense for use in producing an up-to-date optimal estimate of position and velocity. The advantages of the scheme are (1) it provides the best possible estimate (minimum error) based upon ensemble statistics of injection conditions and measurement errors; (2) it is extremely versatile, not requiring adherence to a predetermined observation schedule or reference trajectory; and (3) the computations are sufficiently simple to be practical in an on-board computer. A digital computer simulation of the proposed system is employed to demonstrate the feasibility of an all on-board system and to illustrate the performance attainable in a hypothetical physical situation.

SPACE VEHICLE↗