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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

UTM and D-NET: NASA and JAXA's Collaborative Research on Integrating Small UAS with Disaster Response Efforts

Natural disasters, such as flooding, wildfire, hurricane, tornadoes, earthquakes and tsunamis, pose challenges in preserving human life and minimizing the damages to a region. During catastrophic events, timely response of disaster relief personnel, an efficient deployment of resources in the recovery effort, and coordinated information sharing amongst different relief agencies can make a substantial difference in responding to those impacted by the disaster. Many relief activities currently utilize both ground personnel and manned airborne assets during different phases of the disaster response. Typically, multiple organizations support relief activities and this often creates logistics coordination challenges between agencies which can result in wasted time or resources. The Japan Aerospace Exploration Agency (JAXA) has been developing an "Integrated aircraft operation system for disaster relief (D-NET)", which assists collection and sharing of disaster information through the integrated operation of aircraft such as helicopters, aircraft, and satellites, for efficient and safe rescue operations by disaster relief aircraft. Due to the advancement in unmanned aircraft systems (UAS) technologies, public safety organizations have started incorporating small UAS (sUAS) as an asset in their disasters response activities. To address the airspace integration challenges of the influx of sUAS in the United States the National Aeronautics and Space Administration (NASA), under the UAS Traffic Management (UTM) project, has been engaged in research to enable large-scale commercial applications of sUAS operating in low altitude airspace. This paper presents the integration of D-NET, which incorporate sUAS in the planning, information sharing, and operation support of disasters response activities, and UTM, which provides airspace management to enable large scale high density operations. The integration of the DNET and UTM systems enables coordination, data sharing, and airspace management to improve the timeliness of the disaster response, enable relief organization to reduce cost and overhead by using UAS assets and still maintain airspace safety during the relief activities.

UTM↗
NASA NTRSDate not supplied

Spaceflight Medical Evacuation Risk Assessment Principles – A Qualitative Investigation

Future human space exploration beyond Low Earth Orbit (LEO) will require innovative solutions in many areas, especially to support the crew medically and optimize their health and performance. Challenges will be numerous, including: extended one-way communication delays, minimal to non-existent resupply and a transit time to a “definitive care” facility ranging from 3-days to 9-months. At the same time, exploration spacecraft will face even more significant restrictions on mass-power-volume-data than in present operational settings. Given these limitations, medical risk assessment is of primary importance, especially evaluating the implications of a medical evacuation of an ill or injured crewmember. Such evacuations are complicated and potentially dangerous, and may be impossible in certain phases of the mission, but this must be weighed against the risks of the injured crew remaining aboard a spacecraft with limited medical resources.

A T Almand↗
DOE OSTI2015

A new hybrid genetic algorithm for optimizing the single and multivariate objective functions

In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the most improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.

feedstock↗
DOE OSTI2017

VIPRAM_L1CMS: a 2-Tier 3D Architecture for Pattern Recognition for Track Finding

In HEP tracking trigger applications, flagging an individual detector hit is not important. Rather, the path of a charged particle through many detector layers is what must be found. Moreover, given the increased luminosity projected for future LHC experiments, this type of track finding will be required within the Level 1 Trigger system. This means that future LHC experiments require not just a chip capable of high-speed track finding but also one with a high-speed readout architecture. VIPRAM_L1CMS is 2-Tier Vertically Integrated chip designed to fulfill these requirements. It is a complete pipelined Pattern Recognition Associative Memory (PRAM) architecture including pattern recognition, result sparsification, and readout for Level 1 trigger applications in CMS with 15-bit wide detector addresses and eight detector layers included in the track finding. Pattern recognition is based on classic Content Addressable Memories with a Current Race Scheme to reduce timing complexity and a 4-bit Selective Precharge to minimize power consumption. VIPRAM_L1CMS uses a pipelined set of priority-encoded binary readout structures to sparsify and readout active road flags at frequencies of at least 100MHz. VIPRAM_L1CMS is designed to work directly with the Pulsar2b Architecture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Downhole Sensors in Drilling Operations

Before downhole and surface equipment became mainstream, drillers had little way of knowing where they were or the conditions of the well. Eventually, breakthroughs in technology such as Measurement While Drilling (MWD) devices and the Electronic Drilling Recorder system allowed for more accurate and increased data collection. More modern initiatives that approach drilling as manufacturing such as Lean Drilling, Drilling the Limit, and revitalized Drilling the Limit programs have allowed petroleum drilling operations to become more efficient in the design and creation of a well, increasing rates of penetration by more than 50%. Unfortunately, temperature and cost limitations of these tools have prevented geothermal operations from using this state-of-the-art equipment in most wells. Today, petroleum drilling operations can collect surface measurements on key drilling data such as rotary torque, hook load (for surface weight on bit), rotary speed, block height (for rate of penetration), mud pressure, pit volume, and pump strokes (for flowrates). They also can collect downhole measurements of azimuth, inclination, temperature, pressure, revolutions per minute, downhole torque on bit, downhole weight on bit, downhole vibration, and bending moment using an MWD device (although not necessarily in real time). These data can be used to calculate and minimize mechanical specific energy, which is the energy input required to remove a unit volume of rock. In geothermal operations, these data are not always used due to poor accuracy or lack of equipment. This is one of the major hurdles for geothermal well construction and a reason why geothermal drilling operations take much longer than their petroleum counterparts. This paper reviews the surface and downhole data collection equipment used in the petroleum industry and its associated costs, capabilities, limitations, and impacts. The impact these downhole tools and measurements have had on increasing drilling efficiency for the petroleum industry suggests that developing these tools for high-temperature, high-pressure environments could be similarly impactful for the geothermal industry.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

RL-HEMS: Reinforcement Learning Based Home Energy Management System for HVAC Energy Optimization

Heating, ventilation, and air conditioning (HVAC) is one of the major energy consumers in the residential sector. It is important to be able to monitor and control the energy consumed to provide utility services such as load shaping while satisfying the comfort and economic constraints of the homeowner. The objective of this work is to create the optimal schedule for HVAC operation to reduce the cost while satisfying the home-owner and equipment’s constraints using a model-free Reinforcement Learning (RL)-based optimization. The specific goal is to find the right balance between reducing energy cost, consumption, and customer comfort level. Our research effort addresses this optimization problem using multiple components: the development of initial learning test-bed and implementation of RL techniques on a real home. This will enable the rapid evaluation of the RL techniques and provide an early baseline to train before implementation on site. The RL algorithm is designed to learn the energy use patterns and generate the optimized schedule for HVAC within an acceptable time-interval to satisfy the homeowner’s comfort and minimize the energy usage. Our preliminary results are promising and we have observed a 17% reduction in the total cost and a 15% reduction in the power utilization using our RL-based HVAC model—RL-HEMS.

Kotevska, Olivera↗
DOE OSTI2021

A High-Frequency Planar Transformer with Medium-Voltage Isolation: Preprint

This paper presents the design of a low-loss, high-frequency planar transformer having medium-voltage (10's of kV) isolation capability while transformer primary and secondary windings are interleaved to reduce losses. Medium-voltage isolation between adjacent printed circuit board (PCB) layers is extremely challenging using traditional PCB dielectrics. The isolation requirement is met using PCB with $7$\,kV/mil polyimide (Panasonic Felios RF775) as the dielectric, and by an appropriate layout of the windings and the inter-winding vias. The transformer is used to implement a dual active bridge (DAB) converter in a stackable dc-ac architecture where the dc port is connected to a photovoltaic (PV) string and ac outputs are connected in series to achieve direct PV string-to-medium voltage conversion without the need for low-voltage collection or a bulky line frequency transformer. Since each DAB transformer processes time-varying power, a design methodology is developed to minimize line-cycle-averaged losses. Experimental results are presented for a 1:1 planar transformer in a 7.5\,kW SiC-based dc-to-ac module operating at 200 kHz. Isolation of 26 kV between the primary and secondary layers and between the windings and the core is verified using a hipot tester.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Nonlinear integrable optics beam dynamics experiment and diagnostics

All present circular particle accelerators are built around linear focusing optics. Un-avoidable nonlinear elements appear in accelerators, such as magnetic aberrations and space-charge effects, which are typically corrected using nonlinear magnets. However, these added nonlinearities degrade particle beam stability, and in most cases, the system becomes non-integrable. The Integrable Optics Test Accelerator (IOTA), at Fermi National Accelerator Laboratory (Fermilab), is a test bed to study beam dynamics in integrable lattices for both electron and proton beams, independently. This work presents experimental results of the nonlinear electron beam dynamics behavior in IOTA using an elliptical nonlinear magnet. The elliptical nonlinear magnet allows for a large betatron tune spread, allowing for a stable high-intensity beam. In a future experimental run, minimally invasive beam instrumentation is needed to study time-dependent collective instabilities, and halo formation in space-chargedominated proton beams. Traditional profile monitors are too destructive to the beam or just measure one dimension of the beam. A gas sheet can be injected perpendicular to theproton beam at an angle. By doing so, a two-dimensional, turn-by-turn, transverse profile measurement can be made, which will preserve the integrity of the beam. The developmentand progress of a gas sheet beam profile monitor will also be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Demand-adaptive Transit Design for Urban Transportation Hubs

In this study, we proposed a novel three-stage framework for planning the optimal demand-adaptive transit (DAT) at urban transportation hubs. Given the potential trip demand and road traffic condition, the proposed framework sequentially generates the optimal set of candidate routes, combines the outgoing routes and incoming routes at the hub, and derives the optimal fleet size and corresponding route frequency under the fixed budget. In particular, we build the route generation algorithm which maximizes passenger demand coverage with travel time deviation constraint. And a heuristic algorithm is further developed which yields near-optimal operation routes for real-time demand. The fleet optimization problem is formulated to minimize the weighted cost of energy savings, operation cost and trip revenue. We conduct comprehensive numerical experiments for planning DAT with electric buses at JFK airport in NYC using NYC taxi and for-hire vehicle trip data and GoogleMap speed data. The results show the superior performance of the proposed route generation algorithm which is able to cover citywide passenger demand with only 61 DAT routes. The results also suggest that the proposed DAT planning framework may serve over 47% of existing taxi and FHV demand by operating 18 routes using the fleet of 62 electric buses.

demand adaptive↗
NASA NTRS2016

Tapping the Brake for Entry, Descent, and Landing

A matrix of simulations of hypersonic flow over blunt entry vehicles with steady and pulsing retropropulsion jets is presented. Retropropulsion in the supersonic domain is primarily designed to reduce vehicle velocity directly with thrust. Retropropulsion in the hypersonic domain may enable significant pressure recovery through unsteady, oblique shocks while providing a buffer of reactant gases with relatively low total temperature. Improved pressure recovery, a function of Mach number squared and oblique shock angle, could potentially serve to increase aerodynamic drag in this domain. Pulsing jets are studied to include an additional degree of freedom to search for resonances in an already unsteady flow domain with an objective to maximize the time-averaged drag coefficient. In this paradigm, small jets with minimal footprints of the nozzle exit on the vehicle forebody may be capable of delivering the requisite perturbations to the flow. Simulations are executed assuming inviscid, symmetric flow of a perfect gas to enable a rapid assessment of the parameter space (nozzle geometry, plenum conditions, jet pulse frequency). The pulsed-jet configuration produces moderately larger drag than the constant jet configuration but smaller drag than the jet-off case in this preliminary examination of a single design point. The fundamentals of a new algorithm for this challenging application with time dependent, interacting discontinuities using the feature detection capabilities of Walsh functions are introduced.

Gnoffo, Peter A.↗
NASA NTRS2009

A Mixed Integer Linear Program for Airport Departure Scheduling

Aircraft departing from an airport are subject to numerous constraints while scheduling departure times. These constraints include wake-separation constraints for successive departures, miles-in-trail separation for aircraft bound for the same departure fixes, and time-window or prioritization constraints for individual flights. Besides these, emissions as well as increased fuel consumption due to inefficient scheduling need to be included. Addressing all the above constraints in a single framework while allowing for resequencing of the aircraft using runway queues is critical to the implementation of the Next Generation Air Transport System (NextGen) concepts. Prior work on airport departure scheduling has addressed some of the above. However, existing methods use pre-determined runway queues, and schedule aircraft from these departure queues. The source of such pre-determined queues is not explicit, and could potentially be a subjective controller input. Determining runway queues and scheduling within the same framework would potentially result in better scheduling. This paper presents a mixed integer linear program (MILP) for the departure-scheduling problem. The program takes as input the incoming sequence of aircraft for departure from a runway, along with their earliest departure times and an optional prioritization scheme based on time-window of departure for each aircraft. The program then assigns these aircraft to the available departure queues and schedules departure times, explicitly considering wake separation and departure fix restrictions to minimize total delay for all aircraft. The approach is generalized and can be used in a variety of situations, and allows for aircraft prioritization based on operational as well as environmental considerations. We present the MILP in the paper, along with benefits over the first-come-first-serve (FCFS) scheme for numerous randomized problems based on real-world settings. The MILP results in substantially reduced delays as compared to FCFS, and the magnitude of the savings depends on the queue and departure fix structure. The MILP assumes deterministic aircraft arrival times at the runway queues. However, due to taxi time uncertainty, aircraft might arrive either earlier or later than these deterministic times. Thus, to incorporate this uncertainty, we present a method for using the MILP with "overlap discounted rolling planning horizon". The approach is based on valuing near-term decision results more than future ones. We develop a model of taxitime uncertainty based on real-world data, and then compare the baseline FCFS delays with delays using the above MILP in a simple rolling-horizon method and in the overlap discounted scheme.

Gupta, Gautam↗
NASA NTRS2021

Flood Monitoring and Crop Damage Assessment

In recent years, the occurrence and impact of inland and coastal flood events have become more frequent and damaging, especially within agricultural fields, due to the global climate change and consistent sea level rise. Monitoring and measuring the magnitude of flood events in a timely manner and assessing the subsequent crop damages accurately are precursors in minimizing detrimental consequences that could potentially lead to a global food security crisis. Traditional gauge-based measurements with sophisticated hydrological models are capable of monitoring flood events precisely but limited within the smaller spatial extent, time-consuming, and costly. In recent decades, advancement in airborne- and satellite-based remote sensing technologies offering products at a daily global spatial extent with various spectral resolution helps address the shortcomings of the traditional in situ approaches in flood monitoring. Furthermore, the methods such as classification and band ratioing using remote sensing products are simple and effective in assessing flood-induced agricultural damages. The combination of remote sensing products and geographic information systems along with the current development in web mapping, users now can get near real-time flood monitoring and crop damage assessments, albeit dependent upon the quality of available data. A case study to quantify the impact of the 2011 Missouri Mississippi River flooding on the surrounding cornfield was performed through a regression model. The model was trained using historical daily NDVI and corn yield across Nebraska and Missouri, and the overall accuracy in estimating corn yield was about 90%. The method implemented in this localized case study could be extended at a larger geographical scale.

Flood monitoring↗
DOE OSTI2015

Double resonance fequency light shift compensation in optically oriented laser-pumped alkali atoms

The contributions of the vector and scalar components to the magnetically dependent microwave transition frequency light shift are analyzed and the compensation of these components is experimentally demonstrated for the {sup 87}Rb atoms optically oriented by a laser tuned to the D{sub 2} line of the head doublet. The Allan variance is studied as a function of the averaging time for a tandem of optically pumped quantum magnetometers (OPQMs), one of which is based on a low-frequency spin oscillator while another is based on a quantum microwave discriminator with a resonance frequency that corresponds to magnetically dependent transitions between HFS sublevels with the extremal value of the magnetic quantum number. It is shown that the compensation of the scalar and vector components of the light shift in OPQMs reduces the Allan variance at averaging times that exceed hundreds of seconds compared to a quantum discriminator based on the magnetically independent 0–0 transition. In this case, the minimal Allan variance in OPQMs at the end resonance is achieved at considerably longer averaging times than in the case of the quantum discriminator that is tuned to the 0–0 transition frequency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Advancing subsurface analysis: Integrating computer vision and deep learning for the near real-time interpretation of borehole image logs in the Illinois Basin-Decatur Project

The accurate quantification and mapping of subsurface natural fracture systems using borehole imaging logs are critical for the success of CO 2 sequestration in geologic formations, optimization of engineered geothermal systems, and hydrocarbon production enhancement. However, traditional interpretation processes suffer from time-consuming procedures and human bias. To address these challenges and expedite fracture analysis, we investigated the application of integrated computer vision and DL workflows to automate image log analysis. Specifically, the design of our workflow was crafted to swiftly detect fractures and baffles by using actual electrical resistivity of borehole wall from microresistivity imaging device alongside their binary representation. This novel approach significantly reduces computational time while providing invaluable insights. By incorporating conventional logging and microseismic data, we present a regional subsurface natural fracture mapping technique. Through the minimization of human bias in image log analysis, our automated workflow achieves reduced fracture interpretation time and costs while ensuring robust and reproducible results. We demonstrated the efficacy of our approach by applying the workflow to the Illinois Basin-Decatur Project site. The automated workflow successfully identified major fractured zones, multiple baffles, and an interbedded layer with a high resolution of 0.01 ft or 0.12 in. (0.3 cm) and can be upscaled to any desired resolution. Validation through microseismic and image log interpretations allows for accurate and near-real-time mapping of fractures and baffles, significantly enhancing CO 2 pressure forecasting and postinjection site care. Our approach stands out due to its robustness, consistency, and reduced computational cost compared with alternative feature extraction technologies. It presents exciting possibilities for advancing CO 2 sequestration and engineered geothermal efforts by offering comprehensive and efficient fracture mapping solutions. This technology can contribute significantly to the optimization of CO 2 sequestration projects, facilitating sustainable environmental practices, and combating climate change.

Geochemistry & Geophysics↗
NASA NTRS1977

Stability of numerical integration techniques for transient rotor dynamics

A finite element model of a rotor bearing system was analyzed to determine the stability limits of the forward, backward, and centered Euler; Runge-Kutta; Milne; and Adams numerical integration techniques. The analysis concludes that the highest frequency mode determines the maximum time step for a stable solution. Thus, the number of mass elements should be minimized. Increasing the damping can sometimes cause numerical instability. For a uniform shaft, with 10 mass elements, operating at approximately the first critical speed, the maximum time step for the Runge-Kutta, Milne, and Adams methods is that which corresponds to approximately 1 degree of shaft movement. This is independent of rotor dimensions.

Kascak, A. F.↗
NASA NTRS2006

Optimization of Turbine Rim Seals

Experiments are being conducted to gain an understanding of the physics of rim scale cavity ingestion in a turbine stage with the high-work, single-stage characteristics envisioned for Advanced Subsonic Transport (AST) aircraft gas turbine engines fo the early 21st century. Initial experimental measurements to be presented include time-averaged turbine rim cavity and main gas path static pressure measurements for rim seal coolant to main gas path mass flow ratios between 0 and 0.02. The ultimate objective of this work is develop improved rim seal design concepts for use in modern high-work, single sage turbines n order to minimize the use of secondary coolant flow. Toward this objective the time averaged and unsteady data to be obtained in these experiments will be used to 1) Quantify the impact of the rim cavity cooling air on the ingestion process. 2) Quantify the film cooling benefits of the rim cavity purge flow in the main gas path. 3) Quantify the impact of the cooling air on turbine efficiency. 4) Develop/evaluate both 3D CFD and analytical models of the ingestion/cooling process.

Wagner, J. H.↗
NASA NTRS1997

Ultrasonic wave velocity measurement in small polymeric and cortical bone specimens

A system was refined for the determination of the bulk ultrasonic wave propagation velocity in small cortical bone specimens. Longitudinal and shear wave propagations were measured using ceramic, piezoelectric 20 and 5 MHz transducers, respectively. Results of the pulse transmission technique were refined via the measurement of the system delay time. The precision and accuracy of the system were quantified using small specimens of polyoxymethylene, polystyrene-butadiene, and high-density polyethylene. These polymeric materials had known acoustic properties, similarity of propagation velocities to cortical bone, and minimal sample inhomogeneity. Dependence of longitudinal and transverse specimen dimensions upon propagation times was quantified. To confirm the consistency of longitudinal wave propagation in small cortical bone specimens (< 1.0 mm), cut-down specimens were prepared from a normal rat femur. Finally, cortical samples were prepared from each of ten normal rat femora, and Young's moduli (Eii), shear moduli (Gij), and Poisson ratios (Vij) were measured. For all specimens (bone, polyoxymethylene, polystyrene-butadiene, and high-density polyethylene), strong linear correlations (R2 > 0.997) were maintained between propagation time and distance throughout the size ranges down to less than 0.4 mm. Results for polyoxymethylene, polystyrene-butadiene, and high-density polyethylene were accurate to within 5 percent of reported literature values. Measurement repeatability (precision) improved with an increase in the wave transmission distance (propagating dimension). No statistically significant effect due to the transverse dimension was detected.

Non-NASA Center↗