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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Defining optimal point-to-point transfer surfaces for orbital path-constrained rendezvous

Many scenarios for future orbital operations involve maneuvering in proximity to such large space structures as the Space Station Freedom; in most cases, the accidental contact of a vehicle with such a structure will be dangerous and must be avoided. Classical rendezvous targeting is inadequate for this purpose, because it recognizes no restraint on the path between the point of departure and the desired point of arrival. A computer program has been devised to minimize this susceptibility. Surfaces are found to exist whose penalty is less than that of a sphere, though not markedly less.

Soileau, Kerry M.↗
DOE OSTI2017

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem that requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Co-Optimization Scheme for Hybrid Electric Vehicles Powertrain and Exhaust Emission Control System Using Future Speed Prediction

Hybrid electric vehicles (HEVs) have been an effective solution for improved vehicle fuel efficiency and reduced emission pollution. In this paper, a co-optimization scheme is proposed to optimize fuel efficiency for HEVs. Here, the proposed optimization scheme uses obtainable future speed prediction as the basis to optimally tune control parameters for the existing powertrain control system. The ramp-up time of the catalyst temperature to reach its light-off level in the exhaust emission system is also considered as an additional optimization constraint to reduce emission. The Toyota Prius Hybrid Simulink model which is an integrated model for a powertrain and exhaust emission system is validated using real data from several real driving cycle scenarios. Then, to simplify the formulation of the proposed algorithm, the model for the optimization for powertrain and exhaust emission systems is represented by a set of equivalent neural network (NN) models learned using the data generated from the well-validated Toyota Prius Hybrid Simulink model. Using NN models, a co-optimization algorithm is established that provides an optimal tuning of some fuel-sensitive powertrain control parameters using future speed prediction, leading to a novel co-optimization algorithm, achieving on average a further 9.22% fuel savings for the Toyota Prius Hybrid Simulink model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Decontamination Experiments and Simulations Supporting Recovery After Widespread Contamination - 18685

Clean-up after an uncontrolled nuclear material release differs from common decontamination practices in the nuclear industry and military combat scenarios. Uncontrolled releases, particularly acts of terror, require specific protective actions guides (PAGs) to optimize short and long-term repercussions. Ideally, non-destructive decontamination methods would be employed. To help fulfill this need, the IWATERS (Integrated Wash Aid Treatment Emergency Reuse System) was proposed in 2014 for remediation outside the immediate blast area. 'Wash-Aid' is hosed onto affected areas, and the used wash solution is collected and recycled through sand/clay beds. To help characterize the IWATERS technology, the below was completed: - Decontamination experiments with a pressurized wash solution using Cs-137, Sr- 85, and Eu-152 contaminants on porous urban materials. - Sensitivity analyses on recycling bed variables using GoldSim{sup TM} CT. - A proposed framework that expands the recycling bed model to include probabilistic simulation of immediate recovery efforts. Removal efficacy of tap water and 0.5 M KCl were compared for Cs, Sr, and Eu across asphalt, brick, and concrete. The 0.5 M KCl solution significantly outperformed tap water in every case except for Eu on concrete and Cs on brick. Trends in the high-pressure decontamination with salt additive compared to low pressure decontamination show evidence of physical and chemical removal. Variations in cleaning rate yielded no significant trend. Pressure changes (by adjusting nozzle-to-coupon distance) were only significant for the highest pressure. Hypothetical Contamination Scenario: To tie the decontamination experiments and recycling bed model together, a small contamination scenario was created. Imagine the sides of a small concrete building uniformly contaminated with Cs-137. Power washing the building with 0.5 M KCl solution would result in 857 L of contaminated solution generated in 185 minutes. Two sand clay beds were designed to clean the used solution. With a sand mass fraction of 0.9, a 10 ft{sup 2} bed 4 ft tall could recycle the solution in 1.05 hrs. Changing the sand mass fraction to 0.5 yielded a 2.5 ft{sup 2} bed 4 ft tall (∼55-gallon drum) that recycled the solution in 7.43 hrs. This exercise showed how the sand/clay bed design can easily change to match the primary remediation goals. The second sand/clay bed would reduce the waste generation while the first bed reduces the remediation time. Conclusions: Variations on speed and nozzle distance (pressure) yielded insignificant differences in efficacy except for the closest distance. High-pressure washing showed increased decontamination efficacy with KCl additive in the majority of cases. Except for bed composition, key recycling bed parameters can be varied on-the-fly. This allows for optimization of, for example, time and waste generation. The hypothetical contamination scenario showed pairing decontamination experiment results with modeling tools can lead to increased preparedness for a large-scale contamination event. With collaboration and time, an expanded recovery/remediation model could aid in development of effective protective action guides.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Achievements of actively controlled divertor detachment compatible with sustained high confinement core in DIII-D and EAST

The compatibility of efficient divertor detachment with high-performance core plasma is vital to the development of magnetically controlled fusion energy. The joint research on the EAST and DIII-D tokamaks demonstrates successful integration of divertor detachment with excellent core plasma confinement quality, a milestone towards solving the critical plasma–wall-interaction (PWI) issue and core-edge integration for ITER and future reactors. In EAST, actively controlled partial detachment with T et,div ~ 5 eV around the strike point and H 98 > 1 in different H-mode scenarios including the high β P H-mode scenario have been achieved with ITER-like tungsten divertor, by optimizing the detachment access condition and performing detailed experiments for core-edge integration. For active long-pulse detachment feedback control, a 30 s H-mode operation with detachment-control duration being 25 s has been successfully achieved in EAST. DIII-D has achieved actively controlled fully detached divertor with low plasma electron temperature (T et,div ≤ 5 eV across the entire divertor target) and low particle flux (degree of detachment, DoD > 3), simultaneously with very high core performance (β N ~3, β P > 2 and H 98 ~ 1.5) in the high βP scenario being developed for ITER and future reactors. The high-β P high confinement scenario is characterized by an internal transport barrier (ITB) at large radius and a weak edge transport barrier (ETB, or pedestal), which are synergistically self-organized. Both the high-β P scenario and impurity seeding facilitate divertor detachment. The detachment access leads to the reduction of ETB, which facilitates the development of an even stronger ITB at large radius in the high β P scenario. Thus, this strong large radius ITB enables the core confinement improvement during detachment. In conclusion, these significant joint DIII-D and EAST advances on the compatibility of high confinement core and detached divertor show a great potential for achieving a high-performance core plasma suitable for long-pulse operation of fusion reactors with controllable steady-state PWIs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Physical Layer Security at a Point-to-Point MIMO System With 1-Bit DACs and ADCs

Low-resolution converters reduce the power consumption of wireless devices and help enable large energy-efficient arrays. In this letter, we evaluate the secrecy rate for the extreme case of 1-bit single-user multiple-input multiple-output systems following two signaling approaches. In the first method, the system uses discrete signaling. In the second, the system combines Gaussian signaling with artificial noise alongside power allocation. In the first case, we give a closed-form expression of the secrecy rate and propose an algorithm that provides near-optimal results for low signal-to-noise ratios (SNRs). Further, in the second scenario, depending on the channel state information, we suggest different precoding plans and derive a secrecy rate lower bound. At low SNR, power is allocated to the main signal. Only at high SNR is optimal power allocation effective. Moreover, knowing the eavesdropper channel greatly improves the system’s secrecy.

1-bit digital-to-analog (DAC) and analog-to-digita↗
DOE OSTI2016

TU-H-CAMPUS-JeP3-05: Adaptive Determination of Needle Sequence HDR Prostate Brachytherapy with Divergent Needle-By-Needle Delivery

Purpose: To develop a new method which adaptively determines the optimal needle insertion sequence for HDR prostate brachytherapy involving divergent needle-by-needle dose delivery by e.g. a robotic device. A needle insertion sequence is calculated at the beginning of the intervention and updated after each needle insertion with feedback on needle positioning errors. Methods: Needle positioning errors and anatomy changes may occur during HDR brachytherapy which can lead to errors in the delivered dose. A novel strategy was developed to calculate and update the needle sequence and the dose plan after each needle insertion with feedback on needle positioning errors. The dose plan optimization was performed by numerical simulations. The proposed needle sequence determination optimizes the final dose distribution based on the dose coverage impact of each needle. This impact is predicted stochastically by needle insertion simulations. HDR procedures were simulated with varying number of needle insertions (4 to 12) using 11 patient MR data-sets with PTV, prostate, urethra, bladder and rectum delineated. Needle positioning errors were modeled by random normally distributed angulation errors (standard deviation of 3 mm at the needle’s tip). The final dose parameters were compared in the situations where the needle with the largest vs. the smallest dose coverage impact was selected at each insertion. Results: Over all scenarios, the percentage of clinically acceptable final dose distribution improved when the needle selected had the largest dose coverage impact (91%) compared to the smallest (88%). The differences were larger for few (4 to 6) needle insertions (maximum difference scenario: 79% vs. 60%). The computation time of the needle sequence optimization was below 60s. Conclusion: A new adaptive needle sequence determination for HDR prostate brachytherapy was developed. Coupled to adaptive planning, the selection of the needle with the largest dose coverage impact increases chances of reaching the clinical constraints. M. Borot de Battisti is funded by Philips Medical Systems Nederland B.V.; M. Moerland is principal investigator on a contract funded by Philips Medical Systems Nederland B.V.; G. Hautvast and D. Binnekamp are fulltime employees of Philips Medical Systems Nederland B.V.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2014

Integrated System Modeling for Nuclear Thermal Propulsion (NTP)

Nuclear thermal propulsion (NTP) has long been identified as a key enabling technology for space exploration beyond LEO. From Wernher Von Braun's early concepts for crewed missions to the Moon and Mars to the current Mars Design Reference Architecture (DRA) 5.0 and recent lunar and asteroid mission studies, the high thrust and specific impulse of NTP opens up possibilities such as reusability that are just not feasible with competing approaches. Although NTP technology was proven in the Rover / NERVA projects in the early days of the space program, an integrated spacecraft using NTP has never been developed. Such a spacecraft presents a challenging multidisciplinary systems integration problem. The disciplines that must come together include not only nuclear propulsion and power, but also thermal management, power, structures, orbital dynamics, etc. Some of this integration logic was incorporated into a vehicle sizing code developed at NASA's Glenn Research Center (GRC) in the early 1990s called MOMMA, and later into an Excel-based tool called SIZER. Recently, a team at GRC has developed an open source framework for solving Multidisciplinary Design, Analysis and Optimization (MDAO) problems called OpenMDAO. A modeling approach is presented that builds on previous work in NTP vehicle sizing and mission analysis by making use of the OpenMDAO framework to enable modular and reconfigurable representations of various NTP vehicle configurations and mission scenarios. This approach is currently applied to vehicle sizing, but is extensible to optimization of vehicle and mission designs. The key features of the code will be discussed and examples of NTP transfer vehicles and candidate missions will be presented.

Systems Engineering↗
DOE OSTI2018

Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks

This study develops a tractable formulation for optimal placement and sizing of inverter-based renewable systems in multi-phase distribution networks. The goal of the formulation is to minimize the cost of inverter installation, average power import, and average distributed generation curtailment. Threephase and single-phase inverter models are presented that preserve the underlying mappings between renewable uncertainty to power injection. The uncertainty of distributed generators (DGs) and loads are characterized by a finite set of scenarios. Linear multi-phase power flow approximations are used in conjunction with scenario reduction techniques to arrive at a tractable twostage stochastic formulation for optimal DG placement and sizing. First-stage decisions are locations for DG deployment and capacity sizes, and second-stage decisions include DG real power curtailment, reactive power support, as well as feeder voltage profile. The resulting formulation is a mixed-integer second-order cone program and can be solved efficiently either by existing optimization solvers or by relaxing the binary variables to the [0,1] interval. Simulation studies on standard multi-phase IEEE test feeders promise that optimal stochastic planning of DGs reduces costs during validation, compared to a scheme where uncertainty is only represented by its average value.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Optimal Location of Radiation Therapy Centers With Respect to Geographic Access

Purpose: To develop a framework with which to evaluate locations of radiation therapy (RT) centers in a region based on geographic access. Methods and Materials: Patient records were obtained for all external beam radiation therapy started in 2011 for the province of British Columbia, Canada. Two metrics of geographic access were defined. The primary analysis was percentage of patients (coverage) within a 90-minute drive from an RT center (C90), and the secondary analysis was the average drive time (ADT) to an RT center. An integer programming model was developed to determine optimal center locations, catchment areas, and capacity required under different scenarios. Results: Records consisted of 11,096 courses of radiation corresponding to 161,616 fractions. Baseline geographic access was estimated at 102.5 minutes ADT (each way, per fraction) and 75.9% C90. Adding 2 and 3 new centers increased C90 to 88% and 92%, respectively, and decreased ADT by between 43% and 61%, respectively. A scenario in which RT was provided in every potential location that could support at least 1 fully utilized linear accelerator resulted in 35.3 minutes' ADT and 93.6% C90. Conclusions: The proposed framework and model provide a data-driven means to quantitatively evaluate alternative configurations of a regional RT system. Results suggest that the choice of location for future centers can significantly improve geographic access to RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Assessment of thermal loads in the CERN SPS crab cavities cryomodule 1

As a part of the HL-LHC upgrade, we designed a cryomodule to host two crab cavities for a first test with protons in the SPS machine. The evaluation of the cryomodule heat loads is essential to dimension the cryogenic infrastructure of the system. The current design features two cryogenic circuits. The first circuit adopts superfluid helium at 2 K to maintain the cavities in the superconducting state. The second circuit, based on helium gas at a temperature between 50 K and 70 K, is connected to the thermal screen, also serving as heat intercept for all the interfaces between the cold mass and the external environment. We present an overview of the heat loads to both circuits, and the combined numerical and analytical estimations. The heat load of each element is detailed for the static and dynamic scenarios, with considerations on the design choices for the thermal optimization of the most critical components.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Information flow for security in control systems

This paper considers the development of information flow analyses to support resilient design and active detection of adversaries in cyber physical systems (CPS). CPS security, though well studied, suffers from fragmentation. In this paper, we consider control systems as an abstraction of CPS. Here, we use information flow analysis, a well established set of methods developed in software security, to obtain a unified framework that captures and extends results in control system security. Specifically, we propose the Kullback Liebler (KL) divergence as a causal measure of information flow, which quantifies the effect of adversarial inputs on sensor outputs. We show that the proposed measure characterizes the resilience of control systems to specific attack strategies by relating the KL divergence to optimal detection. We then relate information flows to stealthy attack scenarios where an adversary can bypass detection. Finally, this article examines active detection mechanisms where a defender intelligently manipulates control inputs or the system itself to elicit information flows from an attacker's malicious behavior. In all previous cases, we demonstrate an ability to investigate and extend existing results through the proposed information flow analyses.

Weerakkody, Sean↗
DOE OSTI2019

Economic Optimal Control for Minimizing Fuel Consumption of Heavy-Duty Trucks in a Highway Environment

This paper provides a comparative assessment of three economic optimal control strategies, aimed at minimizing the fuel consumption of heavy-duty trucks in a highway environment, under a representative lead vehicle model informed by traffic data. These strategies fuse a global, offline dynamic programming (DP) optimization with online model predictive control (MPC). We then show how two of the three strategies can be adapted to accommodate the presence of traffic and optimally navigate signalized intersections using infrastructure-to-vehicular (I2V) communication. The MPC optimization, which is local in nature, makes refinements to a coarsely (but globally, subject to grid resolution) optimized target velocity profile from the DP optimization. The three candidate economic MPC formulations that are evaluated include: a nonlinear time-based formulation that directly penalizes predicted fuel consumption, a nonlinear time-based formulation that penalizes braking effort as a surrogate for fuel consumption, and a linear distance-based convex formulation that maintains a tradeoff between energy expenditure and tracking of the coarsely optimized velocity profile obtained from DP. Using a medium-fidelity Simulink model, based on a Volvo truck's longitudinal and engine dynamics, we analyze the optimization's performance on four highway routes under various traffic scenarios. Results demonstrate 3.7-8.3% fuel economy improvement on highway routes without traffic and 6.5-10% on the same routes with traffic included. Furthermore, we present a detailed analysis of energy usage by "type" (aerodynamic losses, braking losses, and comparison of brake-specific fuel consumption), under each candidate control strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

An Improved Genetic Algorithm approach to the Unit Commitment/Economic Dispatch problem

The deployment of new technologies, the importance of accurately modeling the dynamics of the generating units and the introduction of new policies are making the solution of the Unit Commitment/Economic Dispatch problem more and more complicated.In the present scenario, traditionally followed scheduling criteria might not lead to the optimal fleet configuration any more. In addition, most of the widely used techniques have limited capabilities at modeling the nonlinear dynamics of committed power plants. When realistic power systems comprising of several tens of generating units are modeled, the resulting optimization problem turns to be computationally intensive for the current computing capabilities. In this paper, an improved version of a GA-based optimization algorithm is presented. A detailed methodology aimed at obtaining a more efficient version of the GA, and a more detailed and accurate description of the flexible operation flexibility of the power plants is described.

genetic algorithm↗
DOE OSTI2012

Bulk and surface controlled diffusion of fission gas atoms

Fission gas retention and release impact nuclear fuel performance by, e.g., causing fuel swelling leading to mechanical interaction with the clad, increasing the plenum pressure and reducing the gap thermal conductivity. All of these processes are important to understand in order to optimize operating conditions of nuclear reactors and to simulate accident scenarios. Most fission gases have low solubility in the fuel matrix, which is especially pronounced for large fission gas atoms such as Xe and Kr, and as a result there is a significant driving force for segregation of gas atoms to extended defects such as grain boundaries or dislocations and subsequently for nucleation of gas bubbles at these sinks. Several empirical or semi-empirical models have been developed for fission gas release in nuclear fuels, e.g. . One of the most commonly used models in fuel performance codes was published by Massih and Forsberg. This model is similar to the early Booth model in that it applies an equivalent sphere to separate bulk UO 2 from grain boundaries represented by the sphere circumference. Compared to the Booth model, it also captures trapping at grain boundaries, fission gas resolution and it describes release from the boundary by applying timedependent boundary conditions to the circumference. In this work we focus on the step where fission gas atoms diffuse from the grain interior to the grain boundaries. The original Massih-Forsberg model describes this process by applying an effective diffusivity divided into three temperature regimes. In this report we present results from density functional theory calculations (DFT) that are relevant for the high (D 3 ) and intermediate (D 2 ) temperature diffusivities of fission gases. The results are validated by making a quantitative comparison to Turnbull's and Matzke's data. For the intrinsic or high temperature regime we report activation energies for both Xe and Kr diffusion in UO 2±x , which compare favorably to available experiments. This is an extension of previous work. In particular, it applies improved chemistry models for the UO 2±x nonstoichiometry and its impact on the fission gas activation energies. The derivation of these models follows the approach that used in our recent study of uranium vacancy diffusion in UO 2 . Also, based on the calculated DFT data we analyze vacancy enhanced diffusion mechanisms in the intermediate temperature regime. In addition to vacancy enhanced diffusion we investigate species transport on the (111) UO 2 surface. This is motivated by the formation of small voids partially filled with fission gas atoms (bubbles) in UO 2 under irradiation, for which surface diffusion could be the rate-limiting transport step. Diffusion of such bubbles constitutes an alternative mechanism for mass transport in these materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Visualization for Hyper-Heuristics: Front-End Graphical User Interface

Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. While such automated design has great advantages, it can often be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address these issues of usability by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics to support practitioners, as well as scientific visualization of the produced automated designs. My contributions to this project are exhibited in the user-facing portion of the developed system and the detailed scientific visualizations created from back-end data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A Comparison of Genetic Programming Variants for Hyper-Heuristics

Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance in Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Hydropower Value Drivers

Conventional hydro resources generate the majority of their value by providing energy under most conditions, but the relative fraction of value generated by providing ancillary services and capacity increases with increasing penetration of resources with zero fuel costs. Pumped storage hydropower resources generate the majority of their value by providing capacity under most conditions, but the relative fraction of value generated by providing energy increases with increasing penetration of resources with zero fuel costs. The total value of conventional hydropower generally decreases in systems with increasing penetration of resources with zero fuel costs; this is largely due to the associated decrease in average energy prices. The total value of pumped storage generally increases in systems with increasing penetration of resources with zero fuel costs, largely due to opportunities to operate in pumping mode when energy prices are low or even negative. Energy storage representation must be enhanced to ensure that models accurately capture system value streams for these resources. Current power system models have a limited ability to capture the price dynamics of ancillary services, and it is still challenging to assess the role and magnitude of ancillary service value streams in future systems. Power systems are currently in a state of rapid and dramatic evolution due to a number of different factors, including the increasing penetration of variable renewable energy (VRE) sources, such as wind and solar, and battery energy storage systems (BESS). This evolution will change the way power systems are fundamentally planned and operated. Some of these changes may be incremental, while others may be more significant, but the result will likely be parallel evolution in the definition and requirement of different grid services and therefore a subsequent shift in their relative values. This report presents a framework developed to identify such system value drivers and quantify their relative impact on several different value streams, with a specific focus on implications for conventional hydropower and pumped storage hydropower (PSH) resources. This value drivers framework (VDF) encompasses five core analytical steps: 1. Identify potential drivers and develop scenarios, 2. Execute production cost models, 3. Calibrate prices, 4. Optimize hydropower operations, and 5. Quantify value drivers.

13 HYDRO ENERGY↗