SEARCH · Engineering Papers

Results for “Route optimization”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Delay-Based Traffic Signal Control for Throughput Optimality and Fairness at an Isolated Intersection

With the attractive feature of guaranteeing maximum network throughput, backpressure routing has been widely used in wireless communication networks. Motivated by the backpressure routing, in this paper, we propose a delay-based traffic signal control algorithm in transportation networks. We prove that this delay-based control achieves optimal throughput performance, same as the queue-based traffic signal control in the literature. However, a vehicle at a lane whose queue length remains very small may be excessively delayed under the queue-based signal control. Our delay-based backpressure control can deal with the excessive delays and achieve better fairness with respect to delay while still guaranteeing throughput optimality. Moreover, a general weighted control scheme combining the queue-based and delay-based schemes is also investigated, to provide a more flexible control according to the quality of service requirements. Numerical results explore their performance under both homogeneous and heterogeneous traffic scenarios.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

A Method of Optimal Control for Class 8 Vehicle Platoons Over Hilly Terrain

This work develops and implements an NMPC control system to facilitate fuel-optimal platooning of Class 8 vehicles over challenging terrain. Prior research has shown that Cooperative Adaptive Cruise Control (CACC), which allows multiple Class 8 vehicles to follow in close succession, can save between 3 and 8% in overall fuel consumption on flat terrain. However, on more challenging terrain, e.g. rolling hills, platooning vehicles can experience diminished fuel savings, and, in some cases, an increase in fuel consumption relative to individual vehicle operation. This research explores the use of Nonlinear Model Predictive Control (NMPC) with predefined route grade profiles to allow platooning vehicles to generate an optimal velocity trajectory with respect to fuel consumption. In order to successfully implement the NMPC system, a model relating vehicle velocity to fuel consumption was generated and validated using experimental data. Additionally, the predefined route grade profiles were created by using the vehicle's GPS velocity over the desired terrain. The real-time NMPC system was then implemented on a two-truck platoon operating over challenging terrain, with a reference vehicle running individually. The results from NMPC platooning are compared against fuel results from a classical proportional-integral-derivative (PID) headway control method. Furthermore, this comparison yields the comparative fuel savings and energy efficiency benefit of NMPC system. In the final analysis, significant fuel savings of greater than 14 and 20% were seen for the lead and following vehicles relative to their respective traditional cruise control and platooning architectures.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1986

An optimization model for the US Air-Traffic System

A systematic approach for monitoring U.S. air traffic was developed in the context of system-wide planning and control. Towards this end, a network optimization model with nonlinear objectives was chosen as the central element in the planning/control system. The network representation was selected because: (1) it provides a comprehensive structure for depicting essential aspects of the air traffic system, (2) it can be solved efficiently for large scale problems, and (3) the design can be easily communicated to non-technical users through computer graphics. Briefly, the network planning models consider the flow of traffic through a graph as the basic structure. Nodes depict locations and time periods for either individual planes or for aggregated groups of airplanes. Arcs define variables as actual airplanes flying through space or as delays across time periods. As such, a special case of the network can be used to model the so called flow control problem. Due to the large number of interacting variables and the difficulty in subdividing the problem into relatively independent subproblems, an integrated model was designed which will depict the entire high level (above 29000 feet) jet route system for the 48 contiguous states in the U.S. As a first step in demonstrating the concept's feasibility a nonlinear risk/cost model was developed for the Indianapolis Airspace. The nonlinear network program --NLPNETG-- was employed in solving the resulting test cases. This optimization program uses the Truncated-Newton method (quadratic approximation) for determining the search direction at each iteration in the nonlinear algorithm. It was shown that aircraft could be re-routed in an optimal fashion whenever traffic congestion increased beyond an acceptable level, as measured by the nonlinear risk function.

Mulvey, J. M.↗

DOE OSTI2016

Optimization of Material Recycling During the Decommissioning Process of Nuclear Power Plants - 16123

The German Government decided in 2011 to phase out nuclear power. Therefore, in the near future there will be several nuclear power plants queued up, in parallel, for dismantling. In nuclear decommissioning there is no standardized procedure available, so that a high level of optimization potential can be assumed. We present the results of a preliminary study, in which the optimization potential of metal recycling during the dismantling process should be estimated. The project can be roughly divided into four sections: - Determination of the metal inventory of an exemplarily selected plant; - Analysis of the recycling routes of scrap metal fractions and assessment of the potential for optimization of each process step during the dismantling; - Conduction of activation calculations to uncover the potential of interim storage allowing for radioactive decay; - In collaboration with the Institute of Process Metallurgy and Metal Recycling at the RWTH Aachen, appropriate process steps and process chains of an optimized metal recycling for each of the resulting scrap metal fractions are identified. The paper and the presentation summarize the status and the results of the project implementation and will address for the optimization potentials for decommissioning projects. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Joint Optimization of Multimodal Transit Frequency and Shared Autonomous Vehicle Fleet Size with Hybrid Metaheuristic and Nonlinear Programming

Shared autonomous vehicles (SAVs) bring competition to traditional transit services but redesigning multimodal transit network can utilize SAVs as feeders to enhance service efficiency and coverage. This paper presents an optimization framework for the joint multimodal transit frequency and SAV fleet size problem, a variant of the transit network frequency setting problem. The objective is to maximize total transit ridership (including SAV-fed trips and subtracting boarding rejections) across multiple time periods under budget constraints, considering endogenous mode choice (transit, point-to-point SAVs, driving) and route selection, while allowing for strategic route removal by setting frequencies to zero. Due to the problem’s non-linear, non-convex nature and the computational challenges of large-scale networks, we develop a hybrid solution approach that combines a metaheuristic approach (particle swarm optimization) with nonlinear programming for local solution refinement. To ensure computational tractability, the framework integrates analytical approximation models for SAV waiting times based on fleet utilization, multimodal network assignment for route choice, and multinomial logit mode choice behavior, bypassing the need for computationally intensive simulations within the main optimization loop. Applied to the Chicago metropolitan area’s multimodal network, our method illustrates a 33.3% increase in transit ridership through optimized transit route frequencies and SAV integration, particularly enhancing off-peak service accessibility and strategically reallocating resources.

Ng, Max↗

DOE OSTI2014

Electrical properties of samarium cobaltite nanoparticles synthesized using Sol–Gel autocombustion route

Highlights: • The structural evolution and its electrical properties of samarium cobaltite nanograins are discussed. • Optimization of SmCoO{sub 3} nanograins is achieved by post sintering as-prepared gel at 800 °C. • The impedance spectra indicate the semiconducting behavior SmCoO{sub 3} nanograins. - Abstract: Nanograins of SmCoO{sub 3} are prepared by citric acid assisted Sol–Gel autocombustion route. The characterizations of crystal structure, surface morphology and electrical properties of SmCoO{sub 3} powder are done using XRD, HRSEM, FTIR and BDS. The structural evolution of SmCoO{sub 3} upon increasing the annealing temperature is followed using XRD and FTIR analyses. The powder sample contains polycrystalline grains with average size equal to 35 nm and orthorhombic perovskite structure with Pbnm space group. The vibrational bands observed in FTIR spectrum at 545 cm{sup −1} and 439 cm{sup −1} correspond to Co-O stretching modes in cobaltite system. HRSEM images of the sample show the formation of hexagonal shaped grains of samarium cobaltite. The AC electrical conductivity of 4.914 × 10{sup −5} S cm{sup −1} at 295 K is measured for SmCoO{sub 3} nanoparticles. The impedance spectra bring out the semiconducting behavior of the material.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Optimization-Inspired Pin-Fin Array for Supercritical Carbon Dioxide Recuperator

Additively manufactured heat exchangers are one possible route to cost-effective sCO 2 power cycles. In this paper, experimental results are obtained for two helical pin fin tubes that were designed following parametric optimization of the fin array. Neither the numerical optimization nor the experimental testing have been previously reported in the literature. The two tube designs were, (1) the optimization inspired design, and (2) the optimization-inspired design with a fin diameter increased by a factor of 2. To characterize the print, the designs were scanned using X-ray computed tomography to measure feature sizes and heat transfer area. The optimization was conducted in a commercial, computational fluid dynamics code. The code solved the Reynolds Averaged Navier-Stokes (RANS) and energy equations with turbulence closure provided by the shear stress transport (SST) k-ω model. In the experiments, the Nusselt number augmentation was measured using the Wilson plot technique and the friction factor was determined with mass flow and pressure drop measurements. The experimental testing indicated that the optimization-inspired design had a friction factor that was four times less than the baseline tube design at equal Nusselt number. Additionally, the optimization-inspired design had a 14% improvement in Nusselt number, at equal friction factor, relative to the best performing computational fluid dynamics (CFD) trial points. Tube design (2), with the larger diameter pin fins, had similar performance, within experimental error, as the tube with the smaller diameter pin fins (1). Both tubes achieved overall fin array efficiencies near 1. A performance factor, V/V 0 , equal to the volume of the enhanced heat exchanger divided by the volume of the baseline (no-fins) heat exchanger, is recommended to quantify internal cooling performance. In conclusion, the experimental shell and tube heat exchanger, using the additively manufactured tube, is competitive with printed circuit heat exchangers in its pressure drop class and could be further improved by optimizing a shell-and-tube heat exchanger utilizing this heat transfer enhancement feature.

42 ENGINEERING↗

DOE OSTI2025

reVRt (reV Routing) [SWR-25-112]

The reV Routing (reVRt) tool is a computational framework for modeling and optimizing transmission infrastructure requirements for electrical grid connections. By employing a spatially-aware least-cost-path methodology, it allows users to incorporate a wide range of factors including siting constraints, regional component costs, land composition costs, point-of-interconnection costs, and network upgrade costs. Additionally, the tool enables advanced follow-on analyses, such as land characterization for potential transmission line routes, to support informed decision-making. Although it's designed to integrate seamlessly with the reV model, the reV Routing tool is versatile and can also be utilized independently for standalone analyses in transmission planning and resource assessment scenarios.

Pinchuk, Pavlo (Paul) [National Renewable Energy L↗

DOE OSTI2023

Intelligent network slicing and policy-based routing engine

One or more aspects of the present disclosure are directed to network optimization solutions provided as software agents (applications) executed on network nodes in a heterogenous multi-vendor environment to provide cross-layer network optimization and ensure availability of network resources to meet associated Quality of Experience (QoE) and Quality of Service (QoS). In one aspect, a network slicing engine is configured to receive at least one request from at least one network endpoint for access to the heterogeneous multi-vendor network for data transmission; receive information on state of operation of a plurality of communication links between the plurality of nodes; determine a set of data transmission routes for the request; assign a network slice for serving the request; determine, from the set of data transmission routes, an end-to-end route for the network slice; and send network traffic associated with the request using the network slice and over the end-to-end route.

Mody, Apurva N.↗

DOE OSTI2018

Focus optimization at relativistic intensity with high numerical aperture and adaptive optics

Improved focusing of laser beams using high numerical aperture systems is an efficient route to increasing intensities in the ultrafast regime to relativistic levels. We experimentally demonstrate a new method of optimizing the focus of a high-power laser, using second harmonic generation at full intensity in a low-pressure gas to provide a figure of merit for optimizing the shape of a deformable mirror via a genetic algorithm. Nonlinear and thermal aberrations are corrected, and aberrations introduced by filters are avoided. Furthermore, the method is applied to focus a millijoule, short pulse (30 fs), high repetition rate laser system to relativistic intensity in both near IR and mid IR regimes.

Lin, Jinpu↗

DOE OSTI2022

Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles

Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal combustion and electric vehicles. Optimizing the operation of such mixed fleets is challenging because it requires accurate trip-level predictions of electricity and fuel use as well as efficient algorithms for assigning vehicles to transit routes. We present a novel framework for the data-driven prediction of trip-level energy use for mixed-vehicle transit fleets and for the optimization of vehicle assignments, which we evaluate using data collected from the bus fleet of CARTA, the public transit agency of Chattanooga, TN. We first introduce a data collection, storage, and processing framework for system-level and high-frequency vehicle-level transit data, including domain-specific data cleansing methods. We train and evaluate machine learning models for energy prediction, demonstrating that deep neural networks attain the highest accuracy. Based on these predictions, we formulate the problem of minimizing energy use through assigning vehicles to fixed-route transit trips. We propose an optimal integer program as well as efficient heuristic and meta-heuristic algorithms, demonstrating the scalability and performance of these algorithms numerically using the transit network of CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Robotic Software Architecture for in-Space Outfitting Operations

Space exploration is expanding into longer missions, larger payloads, and more complex operations. To make these larger scale missions a reality, it is necessary to perform assembly, construction, and maintenance tasks via a robotic workforce in addition to crewed operations. While there has been significant research into in-space assembly and manufacturing, it is primarily focused on rigid structural elements, such as ISRU printing or truss construction. Outfitting tasks, such as cable routing, are a critical step to a fully operational in-space facility. This paper seeks to provide a reduced order state model and an optimized combination of state-of-the-art robotics algorithms applied to a cable routing scenario. Simulation results are expected to advance approaches to online autonomous robotic manipulation of non-rigid elements.

Amy M Quartaro↗

NASA NTRSDate not supplied

Robotic Software Architecture for In-Space Outfitting Operations

Amy Quartaro↗

DOE OSTI2022

Correlating Electronic Structure and Device Physics with Mixing Region Morphology in High-Efficiency Organic Solar Cells

The donor/acceptor interaction in non-fullerene organic photovoltaics leads to the mixing domain that dictates the morphology and electronic structure of the blended thin film. Initiative effort is paid to understand how these domain properties affect the device performances on high-efficiency PM6:Y6 blends. Different fullerenes acceptors are used to manipulate the feature of mixing domain. It is seen that a tight packing in the mixing region is critical, which could effectively enhance the hole transfer and lead to the enlarged and narrow electron density of state (DOS). As a result, short-circuit current (J SC ) and fill factor (FF) are improved. The distribution of DOS and energy levels strongly influences open-circuit voltage (V OC ). The raised filling state of electron Fermi level is seen to be key in determining device V OC . Energy disorder is found to be a key factor to energy loss, which is highly correlated with the intermolecular distance in the mixing region. A 17.53% efficiency is obtained for optimized ternary devices, which is the highest value for similar systems. The current results indicate that a delicate optimization of the mixing domain property is an effective route to improve the V OC , J SC , and FF simultaneously, which provides new guidelines for morphology control toward high-performance organic solar cells.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Low-field magnetoresistance up to 400 K in double perovskite Sr{sub 2}FeMoO{sub 6} synthesized by a citrate route

A wet-chemistry technique, namely the citrate route, has been used to prepare high-quality polycrystalline samples of double perovskite Sr{sub 2}FeMoO{sub 6}. We report on the evolution of magnetic and magnetoresistive properties of the synthesized samples as a function of three parameters (i) the pH of the starting solution, (ii) the decomposition temperature of the citrate precursors and (iii) the sintering conditions. The low-field magnetoresistance (LFMR) value of our best samples is as high as 5% at room temperature for an applied magnetic field of 1 kOe. Additionally, the distinguishing feature of these samples is the persistence of LFMR, with a reasonably large value, up to 400 K which is a crucial parameter for any practical application. Our study indicates that the enhancement of LFMR observed is due to a good compromise between the grain size distribution and their magnetic polarization. -- Graphical abstract: The microstructure (left panel) and corresponding low-field magnetoresistance of one of the Sr{sub 2}FeMoO{sub 6} samples synthesized in the course of this work. Highlights: • Samples of Sr{sub 2}FeMoO{sub 6} are prepared using a citrate route under varying conditions. • Magnetoresistive properties are improved and optimized. • Low-field magnetoresitence values as large as 5% at 300 K/1 kOe are reported. • Persistence of low-field magnetoresistance up to 400 K.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Enhanced Electrochemical Performance of Disordered Rocksalt Cathodes Enabled by a Graphite Conductive Additive

Cobalt-free cation-disordered rocksalt (DRX) cathodes are a promising class of materials for next-generation Li-ion batteries. Although they have high theoretical specific capacities (>300 mA h/g) and moderate operating voltages (~3.5 V vs Li/Li + ), DRX cathodes typically require a high carbon content (up to 30 wt %) to fully utilize the active material which has a detrimental impact on cell-level energy density. To assess pathways to reduce the electrode’s carbon content, the present study investigates how the carbon’s microstructure and loading (10–20 wt %) influence the performance of DRX cathodes with the nominal composition Li 1.2 Mn 0.5 Ti 0.3 O 1.9 F 0.1 . While electrodes prepared with conventional disordered carbon additives (C65 and ketjenblack) exhibit rapid capacity fade due to an unstable cathode/electrolyte interface, DRX cathodes containing 10 wt % graphite show superior cycling performance (e.g., reversible capacities ~260 mA h/g with 85% capacity retention after 50 cycles) and rate capability (~135 mA h/g at 1000 mA/g). Furthermore, a suite of characterization tools was employed to evaluate the performance differences among these composite electrodes. Overall, these results indicate that the superior performance of the graphite-based cathodes is largely attributed to the: (i) formation of a uniform graphitic coating on DRX particles which protects the surface from parasitic reactions at high states of charge and (ii) homogeneous dispersion of the active material and carbon throughout the composite cathode which provides a robust electronically conductive network that can withstand repeated charge–discharge cycles. Overall, this study provides key scientific insights on how the carbon microstructure and electrode processing influence the performance of DRX cathodes. Based on these results, exploration of alternative routes to apply graphitic coatings is recommended to further optimize the material performance.

25 ENERGY STORAGE↗

NASA NTRS1977

Terrain evaluation and route designation based on noisy rangefinder data

This paper discusses an approach to terrain evaluation and route designation for an autonomous Mars rover. The evaluation procedure simulates movement of the rover over a terrain model estimated from noisy range readings. During the simulated movement a potential path is analyzed for adverse gradients and minimum vehicle body clearance which could inhibit the rover's progress. The route designation scheme employs dynamic programming to select the optimal path based on the evaluation results.

Netch, A.↗

NASA NTRS1985

Performance study of a data flow architecture

Teams of scientists studied data flow concepts, static data flow machine architecture, and the VAL language. Each team mapped its application onto the machine and coded it in VAL. The principal findings of the study were: (1) Five of the seven applications used the full power of the target machine. The galactic simulation and multigrid fluid flow teams found that a significantly smaller version of the machine (16 processing elements) would suffice. (2) A number of machine design parameters including processing element (PE) function unit numbers, array memory size and bandwidth, and routing network capability were found to be crucial for optimal machine performance. (3) The study participants readily acquired VAL programming skills. (4) Participants learned that application-based performance evaluation is a sound method of evaluating new computer architectures, even those that are not fully specified. During the course of the study, participants developed models for using computers to solve numerical problems and for evaluating new architectures. These models form the bases for future evaluation studies.

Adams, George↗