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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Real-time Tumor Oxygenation Changes After Single High-dose Radiation Therapy in Orthotopic and Subcutaneous Lung Cancer in Mice: Clinical Implication for Stereotactic Ablative Radiation Therapy Schedule Optimization

Purpose: To investigate the serial changes of tumor hypoxia in response to single high-dose irradiation by various clinical and preclinical methods to propose an optimal fractionation schedule for stereotactic ablative radiation therapy. Methods and Materials: Syngeneic Lewis lung carcinomas were grown either orthotopically or subcutaneously in C57BL/6 mice and irradiated with a single dose of 15 Gy to mimic stereotactic ablative radiation therapy used in the clinic. Serial [{sup 18}F]-misonidazole (F-MISO) positron emission tomography (PET) imaging, pimonidazole fluorescence-activated cell sorting analyses, hypoxia-responsive element-driven bioluminescence, and Hoechst 33342 perfusion were performed before irradiation (day −1), at 6 hours (day 0), and 2 (day 2) and 6 (day 6) days after irradiation for both subcutaneous and orthotopic lung tumors. For F-MISO, the tumor/brain ratio was analyzed. Results: Hypoxic signals were too low to quantitate for orthotopic tumors using F-MISO PET or hypoxia-responsive element-driven bioluminescence imaging. In subcutaneous tumors, the maximum tumor/brain ratio was 2.87 ± 0.483 at day −1, 1.67 ± 0.116 at day 0, 2.92 ± 0.334 at day 2, and 2.13 ± 0.385 at day 6, indicating that tumor hypoxia was decreased immediately after irradiation and had returned to the pretreatment levels at day 2, followed by a slight decrease by day 6 after radiation. Pimonidazole analysis also revealed similar patterns. Using Hoechst 33342 vascular perfusion dye, CD31, and cleaved caspase 3 co-immunostaining, we found a rapid and transient vascular collapse, which might have resulted in poor intratumor perfusion of F-MISO PET tracer or pimonidazole delivered at day 0, leading to decreased hypoxic signals at day 0 by PET or pimonidazole analyses. Conclusions: We found tumor hypoxia levels decreased immediately after delivery of a single dose of 15 Gy and had returned to the pretreatment levels 2 days after irradiation and had decreased slightly by day 6. Our results indicate that single high-dose irradiation can produce a rapid, but reversible, vascular collapse in tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management

High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. Our comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗
DOE OSTI2017

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed this issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10 .

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Robust Optimization for the Day-Ahead Scheduling of Cascaded Hydroelectric Systems

Uncertain electricity prices resulting from the re-structuring of electricity market have brought new opportu-nities and challenges for hydroelectric producers. This paper presents a data-driven robust optimization approach for the day-ahead scheduling of cascaded hydroelectric systems (CHS) with electricity price uncertainty. In this paper, a minimum volume enclosing ellipsoid (MVEE) is adopted to construct an ellipsoidal uncertainty set that fully identifies and exploits the historical characteristics data. Here, a second-order conic optimization formulation of the robust counterpart is derived for efficient computation. A real-world case study is conducted to demonstrate the capability of the proposed optimization approach compared with the traditional robust optimization approach.

13 HYDRO ENERGY↗
DOE OSTI2022

Managing Power Systems-Induced Wildfire Risks Using Optimal Scheduled Shutoffs

The increasing demands for electricity and the increase in extreme weather conditions are putting unprecedented pressure on our electric grids. Often, this pressure leads to electrical component failures, which might ignite wildfires. This work develops a novel model to balance the reliability of power network operations and the risk of wildfire ignition by opti- mizing the operational schedule of power transmission networks considering time-varying risk measures that include exogenous and operational factors. Energy storage systems are considered to deliver power during peak wildfire hours and enable temporal load shifting. The problem is formulated as a mixed-integer linear program that maximizes a weighted sum of the served power demand and the reduction in grid-induced wildfire risk. The results demonstrate the ability of the model to significantly reduce wildfire risk without considerable load shedding.

power systems operations↗
DOE OSTI2016

Coordinated Scheduling for Interdependent Electric Power and Natural Gas Infrastructures

The extensive installation of gas-fired power plants in many parts of the world has led electric systems to depend heavily on reliable gas supplies. The use of gas-fired generators for peak load and reserve provision causes high intraday variability in withdrawals from high-pressure gas transmission systems. Such variability can lead to gas price fluctuations and supply disruptions that affect electric generator dispatch, electricity prices, and threaten the security of power systems and gas pipelines. These infrastructures function on vastly different spatio-temporal scales, which prevents current practices for separate operations and market clearing from being coordinated. Here in this article, we apply new techniques for control of dynamic gas flows on pipeline networks to examine day-ahead scheduling of electric generator dispatch and gas compressor operation for different levels of integration, spanning from separate forecasting, and simulation to combined optimal control. We formulate multiple coordination scenarios and develop tractable physically accurate computational implementations. These scenarios are compared using an integrated model of test networks for power and gas systems with 24 nodes and 24 pipes, respectively, which are coupled through gas-fired generators. The analysis quantifies the economic efficiency and security benefits of gas-electric coordination and dynamic gas system operation.

03 NATURAL GAS↗
DOE OSTI2016

Efficient Synthesis of Graph Methods: a Dynamically Scheduled Architecture

RDF databases naturally map to a graph representation and employ languages, such as SPARQL, that implements queries as graph pattern matching routines. Graph methods exhibit an irregular behavior: they present unpredictable, fine-grained data accesses, and are synchronization inten- sive. Graph data structures expose large amounts of dy- namic parallelism, but are difficult to partition without gen- erating load unbalance. In this paper, we present a novel ar- chitecture to improve the synthesis of graph methods. Our design addresses the issues of these algorithms with two com- ponents: a Dynamic Task Scheduler (DTS), which reduces load unbalance and maximize resource utilization, and a Hi- erarchical Memory Interface controller (HMI), which pro- vides support for concurrent memory operations on multi- ported/multi-banked shared memories. We evaluate our ap- proach by generating the accelerators for a set of SPARQL queries from the Lehigh University Benchmark (LUBM). We first analyze the load unbalance of these queries, showing that execution time among tasks can differ even of order of magnitudes. We then synthesize the queries and com- pare the performance of the resulting accelerators against the current state of the art. Experimental results show that our solution provides a speedup over the serial implementa- tion close to the theoretical maximum and a speedup up to 3.45 over a baseline parallel implementation. We conclude our study by exploring the design space to achieve maximum memory channels utilization. The best design used at least three of the four memory channels for more than 90% of the execution time.

architecture↗
NASA NTRS2003

Power, data latency, and radio frequnecy interference issues in Mars Realy Network scheduling

At different time periods in the future, missions to Mars will overlap. Previous studies indicate that during such periods, existing deep space communication infrastructure cannot handle all Mars communication needs. A plausible solution is to take into account the end-to-end communication performances of network along with operational constraints, and optimize the resource usage by scheduling communication at highest possible data throughputs. As a result, shorter communication time is required and more missions can be accommodated. This principle is demonstrated in this paper for a Mars relay communication network; a network consisting of multiple surface units and orbiters on Mars and the Deep Space Stations.

power latency RFI Mars Relay Network scheduling↗