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In this first step in the Community Planning for Solar process, we provide guidance on forming a collaborative community Solar Planning Team and identifying initial roles, timelines, and goals.
This guide describes how to conduct a Solar Resource and Infrastructure Assessment. The guide is designed to assist community officials, volunteers, and regional planning agency staff in conducting a preliminary assessment for a municipality, community, or other jurisdiction, based primarily on a desktop analysis of existing documents and data. The guide provides a process that can be used to inventory and describe existing infrastructure, community needs, and resources from the perspective of solar development planning.
The US Department of Energy's Energy Transitions Initiative Partnership Project (ETIPP) works alongside remote and island communities seeking to transform their energy systems and increase energy resilience. The City of McGrath took part in the ETIPP program in 2023-2024. As part of the project, community members formed the McGrath Energy Committee, made up of residents and local stakeholder organizations. The McGrath Energy Committee then worked with technical advisors from regional associations, university programs, and national labs to conduct a baseline energy assessment of the community, organize a community energy education series, identify key focus areas relevant to McGrath, explore funding opportunities, and create the McGrath Community Energy Plan. This plan serves as a foundational guide for future energy projects in the community, aligned with McGrath's long-term energy goal: "to be a catalyst to encourage energy resiliency in our community and the Upper Kuskokwim Region." - November 2024.
Despite tremendous progress in the development of untethered soft robots in recent years, existing systems lack the mobility, model‐based control, and motion planning capabilities of their piecewise rigid counterparts. As in conventional robotic systems, the development of versatile locomotion of soft robots is aided by the integration of hardware design and control with modeling tools that account for their unique mechanics and environmental interactions. Here, a framework for physics‐based modeling, motion planning, and control of a fully untethered swimming soft robot is introduced. This framework enables offline co‐design in the simulation of robot parameters and gaits to produce effective open‐loop behaviors and enables closed‐loop planning over motion primitives for feedback control of a frog‐inspired soft robot testbed. This pipeline uses a discrete elastic rods (DERs) physics engine that discretizes the soft robot as many stretchable and bendable rods. On hardware, an untethered aquatic soft robot that performs frog‐like rowing behaviors is engineered. Hardware validation verifies that the simulation has sufficient accuracy to find the best candidates for sets of parameters offline. The simulator is then used to generate a trajectory library of the robot's motion in simulation that is used in real‐time closed‐loop path following experiments on hardware.
Abstract A key challenge in watershed restoration is identifying the appropriate assessments, data, and analyses needed to identify disrupted natural processes, lost and degraded habitats, and limiting factors to ultimately identify and design successful restoration projects. This has proven particularly challenging for large restoration programs focused on recovery of threatened and endangered salmon and trout where numerous tools, models, and other assessments have been developed to assist with habitat restoration at the watershed, reach, and project scale. Unfortunately, it is often unclear which step in the restoration process these various assessment tools will actually address. To assist with identifying the appropriate assessment tool (e.g., model, data collection, analysis, and survey), we reviewed major categories of watershed restoration assessment tools to determine their goals, inputs, outputs, and their utility in helping plan, prioritize, and implement restoration actions. The major categories of assessment tools reviewed were: (1) life cycle and fish–habitat models, (2) watershed assessment methods and techniques, (3) reach assessments, (4) prioritization tools, and (5) common monitoring methods to identify, prioritize, and plan river and watershed restoration projects. We specifically indicated whether these assessment tools directly or indirectly assisted with the key steps in the restoration process that are required to develop successful restoration plans and projects. These steps involve assessing watershed conditions, identifying limiting habitats and life stages, identifying problems and restoration actions, selecting restoration techniques, prioritizing restoration actions, or designing actual restoration projects. It is important to recognize that no single assessment tool will address all the steps in the restoration process. Selecting appropriate assessment tools requires a clear understanding of the goals of the restoration program and which step in the restoration process will be addressed by a particular tool. We provide recommendations for how restoration practitioners and managers can use our review to help select the appropriate assessment tools needed for their watershed.
Abstract This strategic plan summarizes the major accomplishments achieved in the last quinquennial by the soybean [Glycine max(L.) Merr.] genetics and genomics research community and outlines key priorities for the next 5 years (2024–2028). This work is the result of deliberations among over 50 soybean researchers during a 2‐day workshop in St Louis, MO, USA, at the end of 2022. The plan is divided into seven traditional areas/disciplines: Breeding, Biotic Interactions, Physiology and Abiotic Stress, Functional Genomics, Biotechnology, Genomic Resources and Datasets, and Computational Resources. One additional section was added, Training the Next Generation of Soybean Researchers, when it was identified as a pressing issue during the workshop. This installment of the soybean genomics strategic plan provides a snapshot of recent progress while looking at future goals that will improve resources and enable innovation among the community of basic and applied soybean researchers. We hope that this work will inform our community and increase support for soybean research.
This paper describes a novel approach for generating accurate floor plans and 3D models of building interiors using scanned mesh data. Unlike previous methods, which begin with a high resolution point cloud from a laser range-finder, our approach begins with triangle mesh data, as from a Microsoft HoloLens. It generates two types of floor plans, a “pen-and-ink” style that preserves details and a drafting-style that reduces clutter. It processes the 3D model for use in applications by aligning it with coordinate axes, annotating important objects, dividing it into stories, and removing the ceiling. Its performance is evaluated on commercial and residential buildings, with experiments to assess quality and dimensional accuracy. Our approach demonstrates promising potential for automatic digitization and orientation of scanned mesh data, enabling floor plan and 3D model generation in various applications such as navigation, interior design, furniture placement, facilities management, building construction, and HVAC design.
Purpose: To compare the imaging characteristics of intra-arterial cone-beam computed tomography during hepatic arteriography (CBCTHA) versus intra-arterial computed tomography during hepatic arteriography (CTHA) for intraprocedural transarterial chemoembolization (TACE) planning. Materials and Methods: This single-institution retrospective study included 144 patients (96 men, mean age 67.9 years; 48 women, mean age 62.3 years) who underwent 181 TACE sessions between January 2015 and July 2017. Intraprocedural CBCTHA (111 procedures) or CTHA (70 procedures) was performed for TACE planning. Reformatted maximum intensity projection CBCTHA and CTHA images were reviewed by two radiologists and classified using an ordinal scoring system (for tumor identification, tumor feeder vessel identification, and streaking artifact) and a binary scoring system (for the presence of breathing motion artifact and field of view encompassing the entire liver). Data were analyzed using an F test and a z-score test. Results: There were no significant differences in demographic and tumor characteristics between the CBCTHA and CTHA patient cohorts. CTHA was superior to CBCTHA for tumor identification (P < .0001), tumor feeder vessel identification (P < .05), streaking artifact (P < .0001), and field of view encompassing the entire liver (P < .0001). There was a trend toward a lower frequency of breathing motion artifact with CTHA than with CBCTHA (1.4% vs. 10%; P = .057). Conclusion: CTHA provides improved clinical relevant imaging information compared to CBCTHA for intraprocedural TACE planning. Level of Evidence: Level III, retrospective comparative study.
Purpose: The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Methods and Materials: Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damage simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. Results: We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β){sub X} = 2 Gy. Conclusions: These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization.
Purpose: To evaluate the long-term results of computed tomography (CT)–planned high-dose-rate (HDR) brachytherapy (BT) for treating cervical cancer patients. Methods and Materials: CT-planned HDR BT was performed according to the adapted Group European de Curietherapie-European Society for Therapeutic Radiology and Oncology (GEC-ESTRO) recommendations in 216 consecutive patients with locally advanced cervical cancer, International Federation of Gynecology and Obstetrics (FIGO) stage IB to IVA, who were treated with conformal external beam radiation therapy and concomitant chemotherapy. We analyzed outcomes and late side effects evaluated according to the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer and Subjective, Objective, Management, Analysis evaluation scoring system and compared them with the results from a historical group. Results: The median age was 56 years (range, 32-83 years). The median follow-up time for living patients was 52 months (range 37-63 months). The 5-year cumulative incidence function for the local recurrence rate for patients with FIGO II and III was 5.5% and 20%, respectively (P=.001). The 5-year rates of overall survival (OS) and disease-free survival (DFS) were 66.4% and 58.5%, respectively. The relative risk of failure for OS and DFS for FIGO III in relation to FIGO II was 2.24 (P=.003) and 2.6 (P=.000) and for lymph node enlargement was 2.3 (P=.002) and 2 (P=.006), respectively. In 2 patients, rectovaginal fistula occurred, and in 1 patient, vesicovaginal fistula occurred without local progression. Comparison of late adverse effects in patients treated according to the GEC-ESTRO recommendations and in the historical group revealed a reduction in fistula formation of 59% and also a reduction in rectal grade 3 to 4 late toxicity of >59%. Conclusions: This is the largest report with mature data of CT-planned BT HDR for the treatment of cervical cancer with good local control and acceptable toxicity. In comparison with the historical series, there is a substantial benefit in terms of severe late effects. FIGO III and enlarged lymph nodes in positron emission tomography–CT/CT are negative prognostic factors, both with a relative risk of failure of approximately 2.
By precalculation of an entire set of planning solutions for protons, penalizing them and providing a graphical navigator tool (Automated Treatment Planning [ATP]), we aim to improve the efficiency of the planning procedure for uveal melanoma (UM) and make it independent of treatment planner experience.
The purpose of this study is to compare the quality of trigeminal neuralgia (TN) treatment plans with and without utilizing sector blocking. Twelve patients with 13 cases of TN were evaluated in this retrospective study. Identical magnetic resonance imaging (MRI) contour sets and prescription doses used in treatments were reused for all plans. Treatment plans were compared on the basis of the amount of dose received by critical structures (i.e., brainstem, ipsilateral temporal lobe, optic chiasm, optic nerves, cochlea) and the estimated total treatment time. The use of sector blocking resulted in a statistically significant decrease in the radiation dose to the brainstem but increased doses to the cerebellum and temporal lobe regions. The magnitude of these differences was small and individual patient anatomy specific. The use of sector blocking also resulted in a statistically significant increase in the treatment time. The magnitude of the change in treatment time was dependent on the number of sectors blocked. Our study suggests some potential benefits, as well as disadvantages, to the use of sector blocking in the treatment of TN. Treatment decision needs to be individualized based on the patient's anatomy and overall condition.
Biofuels have the potential to strengthen the U.S. energy supply, enhance energy security, and promote economic development. As the United States continues to expand biofuel production, quantifying resource requirements and location-specific constraints is crucial for planning, siting, and technology development to support long-term viability. Accordingly, this work assesses the life cycle resource consumption (water consumption, and land use), water stress and criteria air pollutants associated with expanded U.S. biofuel production over the 2020–2035 period, based on producers’ plans. We perform a bottom-up technology impact assessment and resource assessment by integrating facility-level production statistics with Argonne’s Research and Development (R&D) GREET model and county-level water-stress characterization factors from Available Water Remaining for the United States (AWARE-US) model. Results suggest that by 2035, biofuels could meaningfully contribute to U.S. energy demand, driven primarily by first-generation and waste-based feedstocks with plans for substantial capacity expansion, although cellulosic and e-fuel technologies remain limited. However, growth must be managed to minimize impacts on water resources and land use. These impacts vary by fuel type and facility location, specifically, projected expansion increases water consumption and can elevate water-stress impacts in certain regions like Nebraska, Kansas, Colorado, Idaho, California and North Texas. Direct land use also increases overall, particularly for first-generation feedstocks such as corn and soybeans. These findings underscore the need for continued technological improvements and innovative strategies to manage resource demands as the industry scales and to support complementary deployment within the evolving U.S. energy system.
The U.S. Inflation Reduction Act of 2022 supports biofuel production expansion through the 45Z clean fuel production tax credit, replacing previous 40A and 40B credits. This follows on the Renewable Fuel Standard from the Energy Policy Act of 2005 and its expansion in 2007. States like California, Oregon, and Washington also offer clean fuel credits. Meanwhile, federal agencies, including the U.S. Department of Energy, have advanced alternative fuel technologies through research and development funding. The surging interest in the biofuel industry has spurred the demand for biofuel supplies in the markets, although achieving profitability for advanced biofuels and low-carbon e-fuels remains challenging. This study aims to track U.S. alternative fuel production capacity expansion plans over the next 10 years and estimate impacts on greenhouse gas (GHG) emissions. By tracking built capacity and industry announcements of planned expansion, this study complements other studies which use models to predict changes in energy technologies and the associated GHG implications. Modeled projections of future technologies are often criticized for over or underestimating the cost and potential role of new technologies. The study focuses on sustainable aviation fuel, renewable diesel, ethanol, biodiesel, and renewable natural gas. Using facility-level data, we conducted a bottom-up analysis linking biofuel production pathways with corresponding pathways and parameterizations in the Argonne R&D GREET model. Results indicate that biofuel capacity could reach 3.8 exajoules in 2035, potentially reducing U.S. GHG emissions by 179 million tonnes, including the full life cycle. This corresponds to a 20% reduction in transportation and 5% in industry sector emissions by 2035, or a 3.6% reduction in economy-wide emissions. Overall, this study shows that while biofuel production capacity in the U.S. is expanding, the capacities remain limited compared to fuel demand. Uncertainty regarding the durability and extension of incentives may be dampening the pace of growth. Meanwhile, demonstrating the commercial potential for alternative fuels and climbing the learning curve for new technologies could lead to an increased pace of expansion in later years. This study offers insights for bioenergy stakeholders, highlighting biofuel technologies' contribution to U.S. energy system and emissions reduction over time based on producers' plans.
Abstract Moving target defence (MTD) has been gaining traction to thwart false data injection attacks against state estimation (SE) in the power grid. MTD actively perturbs the reactance of transmission lines equipped with distributed flexible AC transmission system (D‐FACTS) devices to falsify the attacker's knowledge about the system configuration. However, the existing literature has not systematically studied what influences the detection effectiveness of MTD and how it can be improved based on the topology analysis. These problems are tackled here from the perspective of an MTD plan in which the D‐FACTS placement is determined. We first exploit the relation between the rank of the composite matrix and the detecting effectiveness. Then, we rigorously derive upper and lower bounds on the attack detecting probability of MTDs with a given rank of the composite matrix. Furthermore, we analyse existing planning methods and highlight the importance of bus coverage by D‐FACTS devices. To improve the detection effectiveness, we propose a novel graph theory–based planning algorithm to retain the maximum rank of the composite matrix while covering all necessary buses. Comparative results on multiple systems show the high detecting effectiveness of the proposed algorithm in both DC‐ and AC‐SE.
In this study, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%-15% of all moving vehicles in the Dallas-Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials - a common visualization of arterial signal performance for transportation planning and operations.
A planning framework is developed to optimize runoff control schemes at scales relevant for regional planning at an early stage. The framework employs less sophisticated modeling approaches to allow a practical application in developing regions with limited data sources and computing capability. The methodology contains three interrelated modules: (1)the geographic information system (GIS)-based hydrological module, which aims at assessing local hydrological constraints and potential for runoff control according to regional land-use descriptions; (2)the grading module, which is built upon the method of fuzzy comprehensive evaluation. It is used to establish a priority ranking system to assist the allocation of runoff control targets at the subdivision level; and (3)the genetic algorithm-based optimization module, which is included to derive Pareto-based optimal solutions for mesolevel allocation with multiple competing objectives. The optimization approach describes the trade-off between different allocation plans and simultaneously ensures that all allocation schemes satisfy the minimum requirement on runoff control. Our results highlight the importance of considering the mesolevel allocation strategy in addition to measures at macrolevels and microlevels in urban runoff management. (C) 2016 American Society of Civil Engineers.
The flagship of Fermilab's long term research program is the Deep Underground Neutrino Experiment (DUNE), located Sanford Underground Research Facility (SURF) in Lead, South Dakota, which will study neutrino oscillations with a baseline of 1300 km. The neutrinos will be produced in the Long Baseline Neutrino Facility (LBNF), a proposed new beam line from Fermilab's Main Injector. The physics goals of the DUNE require a proton beam with a power of some 2.4 MW at 120 GeV, which is roughly four times the current maximum power. Here I discuss current performance of the Fermilab proton accelerator complex, our plans for construction of the SRF proton linac as key part of the Proton Improvement Plan-II (PIP-II), outline the main challenges toward multi-MW beam power operation of the Fermilab accelerator complex and the staged plan to achieve the required performance over the next 15 years.