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Conference: 14th International Particle Accelerator Conference Date: May 7th-12th, 2023 Location: Lido di Venezia, Italy Presenter: Evan R Scott
Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.
The U.S. Department of Energy (DOE) promotes the production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement with this mission, Idaho National Laboratory (INL) completes an annual SOT report for biomass feedstock logistics. This report summarizes supply system impacts of Bioenergy Technologies Office (BETO)-funded research and development efforts at INL and elsewhere (such as the High-Tonnage Feedstock Logistics projects (Webb et al. 2013a, Webb et al. 2013b, Webb et al. 2013c, Webb and Sokhansanj 2014, Sokhansanj et al. 2014) that lead to improvements in feedstock supply systems. These include improvements to and observed performance of innovative harvest and collection methods, storage technologies, transportation and handling approaches, and advanced preprocessing technologies. Biomass quality and variability, and the interface between feedstock quality and conversion performance are key drivers in addition to delivered feedstock cost. In this report, we estimate the benefits of R&D improvements to individual supply system unit operations, and present the status of feedstock logistics technology development for converting biomass into biofuels. These analyses are supported by experimental data where possible, and help to align the SOT relative to the cost goals defined in the Multi-Year Program Plan. The 2018 Herbaceous SOT aligned feedstock logistic design with current biorefinery’s design capacity utilized by biochemical conversion platform. Currently biochemical conversion platform utilizes a 725,000 dry ton/year biorefiney design for the techno economic analysis. Hence, feedstock delivered cost in the 2018 Herbaceous SOT is calculated based on biorefinery’s 725,000 dry ton design capacity instead of 800, 000 dry ton capacity utilized in the 2017 Herbaceous SOT. Biomass availabilities in this SOT were updated to year 2018 data from the 2016 Billion-Ton Report (BT16) (DOE 2016a), with the exception of switchgrass, for which the 2018 Herbaceous SOT utilized the 2019 switchgrass availability data from BT16. The BT16 report (DOE 2016a) does not project switchgrass availability in 2018; the soonest switchgrass is available in the BT16 report is 2019. Therefore, availability of switchgrass for this analysis was that projected for 2019. The 2018 Herbaceous SOT incorporates same technologies utilized in the 2017 Herbaceous SOT. However, a sensitivity analysis is performed to understand the impact of variation of process parameters on those technologies on feedstock logistic cost. New R&D data that shows the variations of process parameters affecting process performance is incorporated in the 2018 SOT to measure the variations in delivered feedstock cost. The 2018 Herbaceous SOT has also provided projected delivered feedstock of 2022 design case based on near term technical target under BETO funded R&D project. Finally, updated biorefinery size of 725,000 dry ton/year was incorporated within least-cost formulation model to select optimal siting and depot scales during optimization of the least cost blend. This modification to the optimization algorithm allows the trade-off between the cost of increased supply radius and the savings from selecting biomass from higher producing counties to be assessed. Such optimization has also showed the economic benefit of decentralized depots in comparison to centralized preprocessing co-located with the biorefinery by decoupling the biorefinery and feedstock locations. The 2018 Herbaceous SOT report documents the current modeled cost of a herbaceous feedstock supply system (from harvest to the pretreatment reactor throat, including grower payment) for hydrocarbon fuel production via biochemical conversion, based on equipment and processes now available or potentially available in the near term. The modeled cost also considers both the required quality and the availability of the biomass resources. The 2018 Herbaceous SOT predicts a modeled delivered feedstock cost of $83.67/dry ton (2016$); this is a $0.23/dry ton (2016$) decrease from the 2017 Herbaceous SOT. The modification of biorefinery’s designed capacity and increased projected biomass availability in the same supply shed contributed to this modeled cost reduction. The least-cost formulation model to optimally site and scale local distributed preprocessing depots also contributed to the cost reduction by considering county-level grower payment and distance from the biorefinery as variables in the optimization algorithm. Sensitivity analysis on various process parameters that affect delivered feedstock cost in the 2018 Herbaceous SOT shows that the delivered cost could varies from $80.45-$88.83/dry ton. The top factors that causes such variations are: effective baling rate, bale density, hammer mill throughput, interest rate and storage dry matter loss.
This paper presents a multi-agent reinforcement learning (MARL) approach for controlling adjustable metallic reflector arrays to enhance wireless signal reception in non-line-of-sight (NLOS) scenarios. Unlike conventional reconfigurable intelligent surfaces (RIS) that require complex channel estimation, our system employs a centralized training with decentralized execution (CTDE) paradigm where individual agents corresponding to reflector segments autonomously optimize reflector element orientation in three-dimensional space using spatial intelligence based on user location information. Through extensive ray-tracing simulations with dynamic user mobility, the proposed multi-agent beam-focusing framework demonstrates substantial performance improvements over single-agent reinforcement learning baselines, while maintaining rapid adaptation to user movement within one simulation step. Comprehensive evaluation across varying user densities and reflector configurations validates system scalability and robustness. The results demonstrate the potential of learning-based approaches for adaptive wireless propagation control.
To harness the potential of laser powder bed fusion (LPBF) 316H stainless steel (SS) for use in advanced nuclear reactors, extensive research efforts are needed to develop optimal laser processing parameters and appropriate heat treatments, taking into account various manufacturing platforms and locations. Furthermore, it is crucial to assess the material properties in environments relevant to reactor operating conditions. In collaboration with Oak Ridge National Laboratory (ORNL) and Los Alamos National Laboratory (LANL), Argonne National Laboratory (ANL) is dedicated to gaining insights into how the manufacturing process and post-build treatments impact the performance of LPBF 316H SS. This report provides an overview of ANL's research findings for FY23, focusing on LPBF 316H SS produced using a Renishaw AM400 laser system. Specifically, our research has concentrated on three key areas: 1) Optimum laser processing parameters: Leveraging the high-throughput printing technology, we systematically varied the laser power, exposure time and point distance within the same build. By measuring the as-printed porosity, we identified an optimum printing parameter window that produced materials with near-complete density; 2) Post-built treatment development: Materials printed with the optimum laser parameters underwent treatments including stress relief, solution annealing, and hot isostatic pressing. Subsequently, we fabricated tension, creep, and fatigue specimens from materials subjected to these different conditions. Over the next year, a series of scoping tests will be conducted to facilitate the selection of the most suitable post-build treatment condition; 3) Thermal aging effects on microstructure and properties: thermal aging at 550°C, 650°C and 750°C was conducted on LPBF 316H SS specimens up to 2500 h. Microstructural characterization was performed with electron microscopy, and the evolution of the dislocation cell structures and secondary phases was studied. Microhardness tests and tension tests were conducted to quantify changes in mechanical properties. The results revealed that the aged LPBF 316H SS exhibited a high density of Cr-rich and Mo-rich fine precipitates within grains due to the presence of a high density of dislocations and the globally distributed dislocation cell structures, which served as heterogeneous nucleation sites for secondary phases. Along grain boundaries, a Mo-Cr-rich phase, observed in 750°C-aged conditions, displayed significant thermal coarsening. Throughout the aging process, various mechanisms, including stress relaxation, dislocation cell structure recovery, solution hardening, and precipitation hardening, competed to influence materials strength. These results contribute towards establishing the technical basis for qualifying LPBF 316H SS for advanced nuclear reactor applications.
A coupled thermo-hydro-mechanical (THM) numerical workflow that is capable of modeling seismic slip is critical for the successful development of enhanced geothermal systems (EGS). By integrating key physical processes, this workflow enables accurate simulation of temperature and pressure diffusions, stress changes, and induced seismicity. As a result, it serves as a vital tool for predicting induced seismicity and optimizing reservoir stimulation strategies. The Utah FORGE (Frontier Observatory for Research in Geothermal Energy) project, located near Milford, Utah, is a U.S. Department of Energy initiative aimed at advancing EGS technology. In April 2024, eight new stimulation stages (Stages 3R-10) were conducted in well 16A (injection well) subsequent to the first series of stimulation (Stages 1-3) performed in April, 2022. To monitor the induced seismicity, geophones were deployed in wells 58-32, 56-32, and 78B-32, while fiber optic cables were also installed in wells 16B, 78-32, and 78B-32 to collect microseismic data and detect frac hits Preliminary analyses of microseismic catalogs and fiber optic data suggest that the stimulated fractures in Stages 3R–6 closely align with that generated during Stage 3, indicating that the new stimulations were likely reactivating the previously stimulated fracture. To better understand the underlying process, a comprehensive modeling approach that can accurately capture thermal, hydrological, mechanical, and seismic responses is essential. In this work, we propose and utilize a coupled thermo-hydro-mechanical and earthquake (THM+E) simulation workflow to numerically investigate the stimulation activities on well 16A. The specific objective is to confirm whether the new stimulation stages (Stages 3R–6) reactivated fractures previously stimulated during Stage 3. For this purpose, we perform THM+E simulations individually for Stages 3, 3R, 4, and 5, incorporating the discrete fracture networks (DFNs) created by the plane-fitting technique based on the microseismic catalogs. The simulation workflow consists of two separate models: a THM model and an earthquake model, coupled in a one-way manner. Detailed descriptions of the workflow are provided in Section 3. Simulation results are presented in terms of injection pressure, permeability evolution, and predicted seismic catalogs, which are then compared with field data for further analyses. This report is structured as follows. In Section 2, we present detailed analyses of the field data and propose the hypothesis that the new stimulation stages (Stages 3R–6) were probably reactivating the previously stimulated fractures in Stage 3. In Section 3, we introduce the coupled THM+E workflow and the problem setup to validate our hypothesis, followed by the simulation results for each stage in Section 4. Meanwhile, discussions are included to analyze the model predictions and their comparison with field data. Lastly, we conclude the report and outline future plans in Section 5.
The co-location of marine energy and aquaculture is a concept of increasing value and interest in the United States, as the desire for sustainably produced seafood and renewable energy continues to grow. With both industries being fairly nascent in their national development and facing challenges, the deployment of a wave-powered aquaculture farm requires numerous considerations. This report analyzes the energy demands of an integrated multi-trophic aquaculture system at various farm scales and discusses the preliminary technical, regulatory, and logistical considerations required for a co-located deployment. A pilot-scale deployment is outlined with potentially ideal characteristics, and an optimized planning and permitting approach is introduced.
Channel 5 and 7 LANDSAT imagery at the scale of 1:250,000 made during passes in the dry and rainy seasons were used to select the optimal season for cerrado characterization in Mato Grosso do Sul State. The study area is located around the cities of Campo Grande and Tres Lagoas, a region being used for reforestation and rangeland activities. Imagery acquired during the dry season permitted a good discrimination between "cerrado" (woodsy pasture) vegetation and reforestation. In relation to the altered areas, only the recently modified area presented good discrimination of cerrado vegetation. Imagery of the rainy season did not provide a reasonable separation between cerrado and reforestation areas but the altered area could be easily discriminated.
Space-time Data Fusion (STDF) is a methodology for combing heterogeneous remote sensing data to optimally estimate the true values of a geophysical field of interest, and obtain uncertainties for those estimates. The input data sets may have different observing characteristics including different footprints, spatial resolutions and fields of view, orbit cycles, biases, and noise characteristics. Despite these differences all observed data can be linked to the underlying field, and therefore the each other, by a statistical model. Differences in footprints and other geometric characteristics are accounted for by parameterizing pixel-level remote sensing observations as spatial integrals of true field values lying within pixel boundaries, plus measurement error. Both spatial and temporal correlations in the true field and in the observations are estimated and incorporated through the use of a space-time random effects (STRE) model. Once the models parameters are estimated, we use it to derive expressions for optimal (minimum mean squared error and unbiased) estimates of the true field at any arbitrary location of interest, computed from the observations. Standard errors of these estimates are also produced, allowing confidence intervals to be constructed. The procedure is carried out on a fine spatial grid to approximate a continuous field. We demonstrate STDF by applying it to the problem of estimating CO2 concentration in the lower-atmosphere using data from the Atmospheric Infrared Sounder (AIRS) and the Japanese Greenhouse Gasses Observing Satellite (GOSAT) over one year for the continental US.
Structural optimization of a hingeless rotor is investigated to reduce oscillatory hub loads while maintaining aeroelastic stability in forward flight. Design variables include spanwise distribution of nonstructural mass, chordwise location of blade center of gravity and blade bending stiffnesses (flap, lag and torsion). A comprehensive aeroelastic analysis of rotors, based on a finite element method in space and time, is linked with optimization algorithms to perform optimization of rotor blades. Sensitivity derivatives of blade response, hub loads, and eigenvalues with respect to the design variables are derived using a direct analytical approach, and constitute an integral part of the basic blade response and stability analyses. This approach reduces the computation time substantially; an 80 percent reduction of CPU time to achieve an optimum solution, as compared to the widely adopted finite difference approach. Through stiffness and nonstructural mass distributions, a 60-90 percent reduction in all six 4/rev hub loads is achieved for a four-bladed soft-inplane rotor.
A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.
Designers of utility-scale solar plants with storage, seeking to maximize some aspect of plant performance, face multiple challenges. In many geographic locations, there is significant penetration of photovoltaic generation, which depresses energy prices during the hours of solar availability. An energy storage system affords the opportunity to dispatch during higher-priced time periods, but complicates plant design and dispatch decisions. Solar resource variability compounds these challenges, because determining optimal system sizes requires simultaneously considering how the plant will be operated under the imposed market and weather conditions. We develop an approach to analyze the economic performance of hybrid and single-technology solar power plants, which incorporates optimal dispatch, and considers the expected electricity market and weather conditions. We utilize the System Advisor Model software package to simulate the operation of multiple renewable generation and energy storage technologies, in conjunction with hourly-fidelity generation decisions determined by a revenue-maximizing, mixed-integer linear program. We show that, under our assumed market and weather conditions, the lifetime benefit-to-cost ratio can be improved by 6 to 19 percent, relative to a baseline design without optimizing, and that a concentrating solar power with thermal energy storage design produces significantly more energy per year, but is less profitable under our cost assumptions.
The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.
Pioneer, a next-generation single-crystal neutron diffractometer, is under development for Oak Ridge National Laboratory’s Second Target Station. Designed to address a wide range of scientific questions, Pioneer will deliver homogeneous neutron beams with customizable size and divergence and provide a polarized beam option. This article introduces its incident beam optics, highlighting the optimization methodology and the simulated performance. Pioneer will utilize a modified elliptical-straight guide for neutron transport and deploy slit packages and insertable apertures to control beam size and divergence. The optimized guide geometry matches the optimal-and-full-sample-illumination condition, and the beam control system effectively filters out unwanted neutrons while preserving the desired ones. In addition, we have found that polygon-approximated guides provide satisfactory transport efficiency and beam homogeneity, eliminating the need for truly curved guides. Further, to enhance neutronics performance and reduce cost, the coatings of supermirror elements are individually optimized to the lowest half-integer m-values that are sufficient to deliver the desired neutrons. After evaluating polarizing V-cavities and 3 He spin filters over the default polarized wavelength band of 1.2–5.5 Å, we selected a translatable multichannel polarizing V-cavity as the incident beam polarizer. Strategically placed at a location where the beam divergence is low and a large in-guide gap has negligible impact on transport efficiency, the optimized V-cavity achieves an average P 2 T of ~35%.
Despite the long history of hydraulic fracturing, the optimal number of fracturing stages during multi-stage fracture stimulation in horizontal wells can be a complex subject. In addition to the increased expense of multistage fracturing in horizontal wells, increasing the number of fracturing stages does not always correlate with a commensurate increase in production. The problem is the application of a uniform fracture stimulation design to all stages with no consideration for geological variations along the wellbore. The result is an inefficient use and costly waste of energy and water. Optimization of the fracturing process requires an understanding of the cause-and-effect relationship between fracturing parameters and local geological properties at a given location along the wellbore. Realizing that the generalized rock mechanics theories and hypotheses are not truly applicable to fractured and laminated shales, quantifiable impacts of a shale’s geomechanical and depositional features are a prerequisite for design and implementation of optimized hydraulic fractures. The overarching goal of this project is to understand and define the relationships of shale geology and fracture dynamics using detailed field data that includes coring of the fracture domain. Finally, resource recovery from shale formations is estimated to be less than fifteen percent. Research proposed in this project will establish the foundations for investigating enhanced recovery techniques for increased resource recovery in existing fracture treated wells. Natural gas as an EOR fluid is in the initial stages of being used broadly in the oil and gas industry and as such, many aspects of the process need to be researched and addressed prior to widespread acceptance. In addition, re-fracturing techniques, particularly using cemented liners also need to be further investigated. This project explores several of these EOR techniques in greater detail, not just at the theoretical level, but through actual field test sites. This report delves into the research program, identified tasks, several studies, observations, results, and conclusions under the Hydraulic Fracturing Test Site (HFTS) project. This test project is subdivided into three distinct phases and each phase is discussed in detail under separate sections. The original test site for Phase 1 as well as the Phase 2 site are in Midland Basin in Texas and operated by Laredo Petroleum. In the first two phases, the program targeted the Wolfcamp formation in Midland Basin. Phase 3 of the study targeted the EagleFord play in South Texas with Devon Energy as the operator. Significant conclusions from this study include: 1) lateral and vertical fracture growth mapping as well as proppant transport behavior, 2) Use of field gas and its applicability for huff n puff EOR injection in the Midland Basin, 3) Development and validation of proppant log, both at core scale as well as in-fill well implementation by analyzing drilling mud return samples, 4) Applicability of liner refracturing including best practices for enhanced unit level productivity. This report will detail all these studies as well as technical results and conclusions from said studies. These include general subsurface characterization work, completion designs as implemented, studies looking at fracture geometry, high resolution microseismic study, advanced crosswell strain mapping studies including drainage characterization, core characterization results, proppant analysis (core and observation wells), geochemistry, etc. to name a few.
An identification procedure proposed by Shen and Taylor to determine the crack characteristics (location and size of the crack) from dynamic measurements is tested. This procedure was based on minimization of either the 'mean-square' measure of difference between measurement data (natural frequencies and mode shapes) and the corresponding predictions obtained from the computational model. The procedure is tested for simulated damage in the form of symmetric cracks in a simply-supported Bernoulli-Euler beam. The sensitivity of the solution of damage identification problems to the values of parameters that characterize damage is discussed. A sensitivity formula is derived.
Ground-based networks of co-located space geodetic techniques (VLBI, SLR, GNSS. and DORIS) are the basis for the development and maintenance of the International Terrestrial Reference frame (ITRF), which is our metric of reference for measurements of global change, The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) has established a task to develop a strategy to design, integrate and maintain the fundamental geodetic network and supporting infrastructure in a sustainable way to satisfy the long-term requirements for the reference frame. The GGOS goal is an origin definition at 1 mm or better and a temporal stability on the order of 0.1 mm/y, with similar numbers for the scale and orientation components. These goals are based on scientific requirements to address sea level rise with confidence, but other applications are not far behind. Recent studies including one by the US National Research Council has strongly stated the need and the urgency for the fundamental space geodesy network. Simulations are underway to examining accuracies for origin, scale and orientation of the resulting ITRF based on various network designs and system performance to determine the optimal global network to achieve this goal. To date these simulations indicate that 24 - 32 co-located stations are adequate to define the reference frame and a more dense GNSS and DORIS network will be required to distribute the reference frame to users anywhere on Earth. Stations in the new global network will require geologically stable sites with good weather, established infrastructure, and local support and personnel. GGOS wil seek groups that are interested in participation. GGOS intends to issues a Call for Participation of groups that would like to contribute in the network implementation and operation. Some examples of integrated stations currently in operation or under development will be presented. We will examine necessary conditions and challenges in designing a co-location station.
More sustainable agricultural methods are needed to alleviate the decreases in biodiversity and ecosystem services that have occurred because of industrial agriculture. One such method is the inclusion of alternative crops into croplands that can support biodiversity, reduce erosion and chemical runoff, and sequester carbon in the soil. However, the question of where such crops should be planted to balance competing economic and environmental objectives remains open. To this end, we develop a mixed-integer quadratically constrained program to optimize the layout of a cropland considering economic, biodiversity, greenhouse gas emissions, and water quality objectives. We include spatially varying fertilization as a decision variable in addition to crop establishment location. We further include the effect of core area and edges between different crops on biodiversity. To demonstrate the applicability of the model, we apply it to an example field, showing how the optimal cropland design changes as a decision-maker prioritizes different objectives and as edges have different impacts on biodiversity.