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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 127 records · Page 7

Post-Fire Safe Shutdown Capability. An Inspector's Handbook. Draft Report

The Nuclear Regulatory Commission's (NRC) current fire protection regulatory framework was initiated in response to a cable fire that occurred at the Browns Ferry Nuclear Power Station in 1975. Following the issuance of several guidance documents, in 1981 the Commission codified deterministic requirements to provide reasonable assurance that fire would not jeopardize reactor safety (10 CFR 50.48 "Fire Protection" and Appendix R to 10 CFR 50). Since then, the results of plant operating experience, NRC inspection activities and cable fire testing programs have served to clarify the application of these requirements. In 2004, the NRC amended 10 CFR Part 50.48 to add a new subsection, 10 CFR 50.48(c), that endorses, with exceptions, the National Fire Protection Association's 805, "Performance-Based Standard for Fire Protection for Light Water Reactor Electric Generating Plants — 2001 Edition," as a voluntary alternative for demonstrating compliance with Appendix R. To date, approximately half of all operating plants have transitioned to a risk-informed approach under 10 CFR 50.48(c). Regardless of the selected approach, each operating nuclear power plant should establish a comprehensive fire protection program that includes features needed to minimize the likelihood and consequence of firesl. To achieve this objective, fire protection programs integrate the NRC's long-held safety concept of defense-in-depth (DID) by providing multiple barriers against potentially unacceptable consequences of fire. To minimize the frequency and size of fires, the first lines of defense include controls for fire prevention, such as controlling combustibles and ignition sources and fire mitigation features, such as fire detection and suppression systems. In the unlikely event that a fire should start and continue to grow in spite of these features, appropriate fire protection features, such as fire-rated barriers are provided as necessary to ensure the accomplishment of essential shutdown functions. This handbook was specifically developed for NRC inspectors that may be assigned to perform elements of Inspection Procedure (IP) 71111.05T, "Fire Protection (Triennial)," including, (a) "Protection of Safe Shutdown Capabilities," (e) "Alternative Shutdown Capability," and (f) "Circuit Analyses." Thus, the document concentrates solely on the final element of defense-in-depth— ensuring reactor safety will not be compromised in the event of a serious fire. In addition to describing how the NRC's regulatory framework has evolved since the Browns Ferry Fire, the handbook illustrates the content and scope of various analyses typically referenced in a plant's fire protection licensing basis and includes techniques and insights for assessing the plant's conformance to those criteria.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Model predictive control for active insulation in building envelopes

Active insulation systems (AISs) refer to building envelopes with insulation materials that can change their thermal conductivity and are coupled with thermal mass to reduce building energy consumption and peak power. In this research, a novel optimal control approach is proposed to evaluate the maximum theoretical energy and cost-saving potential of AISs. A time-varying model predictive control (TV-MPC) controller was used to optimally select the AIS mode and simultaneously determine the operation of the heating, ventilation and air conditioning (HVAC) system so that the maximum saving potential of the entire system can be realized. To comprehensively evaluate the power shifting flexibility of AISs, two optimization objectives—minimizing weekly electric energy consumption and minimizing weekly electricity cost—were considered. The summer season simulation results show that under the first objective, more than 50% electric and thermal energy was saved when the upper boundary of the indoor air temperature was set to 25 °C. Furthermore under the second optimization objective, 38% of the cost was saved. It can be expected that the developed approach can be easily applied to multiple types of AISs with different mechanisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SPISEA: A Python-based Simple Stellar Population Synthesis Code for Star Clusters

We present Stellar Population Interface for Stellar Evolution and Atmospheres (SPISEA), an open-source Python package that simulates simple stellar populations. The strength of SPISEA is its modular interface which offers the user control of 13 input properties including (but not limited to) the initial mass function, stellar multiplicity, extinction law, and the metallicity-dependent stellar evolution and atmosphere model grids used. The user also has control over the initial–final mass relation in order to produce compact stellar remnants (black holes, neutron stars, and white dwarfs). We demonstrate several outputs produced by the code, including color–magnitude diagrams, HR-diagrams, luminosity functions, and mass functions. SPISEA is object-oriented and extensible, and we welcome contributions from the community. The code and documentation are available on GitHub (https://github.com/astropy/SPISEA) and ReadtheDocs (https://spisea.readthedocs.io/en/latest/), respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

A search for microscopic black holes, string balls, and sphalerons in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for microscopic black holes, string balls, and electroweak sphalerons using proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the CMS detector at the CERN LHC during the 2016–2018 data taking, and corresponding to an integrated luminosity of 138 fb −1 , is presented. Two search strategies based on control samples in data are used. Model-independent limits on the cross section of physics phenomena with multiple energetic jets, leptons, and photons are set using a method that relies on the shape invariance of the scalar sum of the transverse momenta of all objects in the event. Model-dependent limits on black hole and sphaleron production are set using a newly introduced method that has been developed for the identification of collider events with distinct kinematic features by separating them into classes based on phase space proximity. In the context of models with large extra dimensions, semiclassical black holes and string balls with masses below 8.4–11.4 TeV and 9.0–10.7 TeV, respectively, are excluded at 95% confidence level, significantly extending the reach beyond previous searches. Results of a dedicated search for electroweak sphalerons are used to derive an upper limit of 0.0034 at 95% confidence level on the fraction of quark-quark interactions, with a center-of-mass energy above the nominal sphaleron transition energy threshold of 9 TeV, that result in a sphaleron transition.

Beyond Standard Model↗

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗

SU-F-T-501: Dosimetric Comparison of Single Arc-Per-Beam and Two Arc-Per-Beam VMAT Optimization in the Monaco Treatment Planning System

Purpose: The purpose of this study was to evaluate the dosimetric and practical effects of the Monaco treatment planning system “max arcs-per-beam” optimization parameter in pelvic radiotherapy treatments. Methods: A total of 17 previously treated patients were selected for this study with a range of pelvic disease site including prostate(9), bladder(1), uterus(3), rectum(3), and cervix(1). For each patient, two plans were generated, one using a arc-per-beam setting of ‘1’ and another with setting of ‘2’. The setting allows the optimizer to add a gantry direction change, creating multiple arc passes per beam sequence. Volumes and constraints established from the initial clinical treatments were used for planning. All constraints and dose coverage objects were kept the same between plans, and all plans were normalized to 99.7% to ensure 100% of the PTV received 95% of the prescription dose. We evaluated the PTV conformity index, homogeneity index, total monitor units, number of control points, and various dose volume histogram (DVH) points for statistical comparison (alpha=0.05). Results: We found for the 10 complex shaped target volumes (small central volumes with extending bilateral ‘arms’ to cover nodal regions) that the use of 2 arcs-per-beam achieved significantly lower average DVH values for the bladder V20 (p=0.036) and rectum V30 (p=0.001) while still meeting the high dose target constraints. DVH values for the simpler, more spherical PTVs were not found significantly different. Additionally, we found a beam delivery time reduction of approximately 25%. Conclusion: In summary, the dosimetric benefit, while moderate, was improved over a 1 arc-per-beam setting for complex PTVs, and equivalent in other cases. The overall reduced delivery time suggests that the use of multiple arcs-per-beam could lead to reduced patient on table time, increased clinical throughput, and reduced medical physics quality assurance effort.

60 APPLIED LIFE SCIENCES↗

Convex Relaxation of Grid-Connected Energy Storage System Models With Complementarity Constraints in DC OPF

Including complementarity constraints in energy storage system (ESS) models in optimization problems ensure an optimal solution will not produce a physically unrealizable control strategy where there is simultaneous charging and discharging. However, the current approaches to impose complementarity constraints require the use of non-convex optimization methods. Here, we propose a convex relaxation for a common ESS model that has terms for both charging and discharging based on a penalty reformulation for use in a model predictive control (MPC) based optimal power flow (DC OPF) problem. In this approach, the complementarity constraints are omitted and a penalty term is added to the optimization objective function. For the DC OPF problem, we provide analysis for the conditions under which the convex relaxation of the complementarity constraint ensures that a solution with simultaneous ESS charging and discharging operation is suboptimal. Simulation results demonstrating ESS behavior with and without the penalty reformulation are provided for an MPC-based DC OPF problem on multiple IEEE test systems.

25 ENERGY STORAGE↗

3D printing technologies for electrochemical energy storage

Fabrication of electrodes and electrolytes play an important role in promoting the performance of electrochemical energy storage (EES) devices such as batteries and supercapacitors. Traditional fabrication techniques have limited capability in controlling the geometry and architecture of the electrode and solid-state electrolytes, which would otherwise compromise the performance. 3D printing, a disruptive manufacturing technology, has emerged as an innovative approach to fabricating EES devices from nanoscale to macroscale and from nanowatt to megawatt, providing great opportunities to accurately control device geometry (e.g., dimension, porosity, morphology) and structure with enhanced specific energy and power densities. Moreover, the additive manufacturing nature of 3D printing provides excellent controllability of the electrode thickness with much simplified process in a cost effective manner. With the unique spatial and temporal material manipulation capability, 3D printing can integrate multiple nanomaterials in the same print, and multi-functional EES devices (including functional gradient devices) can be fabricated. Herein, we review recent advances in 3D printing of EES devices. We focused on two major 3D printing technologies including direct writing and inkjet printing. The direct material deposition characteristics of these two processes enable them to print on a variety of flat substrates, even a conformal one, well suiting them to applications such as wearable devices and on-chip integrations. Other potential 3D printing techniques such as freeze nano-printing, stereolithography, fused deposition modeling, binder jetting, laminated object manufacturing, and metal 3D printing are also introduced. The advantages and limitations of each 3D printing technology are extensively discussed. More importantly, we provide a perspective on how to integrate the emerging 3D printing with existing technologies to create structures over multiple length scale from macro to nano for EES applications.

3D printing↗

Coordinated Frequency Regulation in Grid-Forming Storage Network via Safety-Consensus

Inverter-based storages are poised to play a prominent role in future power grid with massive renewable generation. Grid-forming inverters (GFMs) are emerging as a dominant technology with synchronous generators (SG)-like characteristics through primary control loops. Advanced secondary-layer control schemes, e.g., consensus algorithms, allow GFM-interfaced storage units to participate in frequency regulations and restore nominal frequency following grid disturbances. However, it is imperative to ensure critical frequency safety limits are not violated while the grid transitions from pre- to post-disturbance operating point. This paper presents a novel safety-enforced consensus method, having three distinct objectives: safe transient frequency evolution, minimizing frequency deviation, and coordinated power sharing. The proposed technique is illustrated using a GFM-interfaced grid-wide storage network on the IEEE 68-bus system under multiple grid transient scenarios.

consensus control↗

Uncertainty quantification and sensitivity analysis of a nuclear thermal propulsion reactor startup sequence

The research presented in this article describes progress in applying stochastic methods, uncertainty quantification, parametric studies, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated via the radiation transport code Griffin to simulate neutronics. Our goal is to develop a reduced-order (surrogate) model that can be rapidly sampled with perturbations to multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums (CDs), which is itself controlled by a hybrid proportional-integral-derivative (PID) controller actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time [Λ] and effective delayed neutron fraction [ β eff ] from a transient Griffin simulation executed via Griffin’s improved quasi-static solver to provide the kinetic parameters) as inputs to functions that control the CD rotation angle. By investigating numerous stochastic approaches, we developed a dual-purpose surrogate model of the NTP system, using polynomial regression in the Multiphysics Object-Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM). The trained model can be rapidly sampled while simultaneously perturbing various input parameters, such as coefficients on the PID control or temperature (directly affecting the neutron cross section). The surrogate model delivers accurate (within 5%) results at speeds orders of magnitude faster (minutes, not days of computational time) than the base model. Once the surrogate model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs as well as the effects of these inputs on the model output. For example, coefficients used in the PID control system may vary due to some type of physical interference, or uncertainty may exist in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters, and operational boundaries can be determined. The goal of this work is to support development of an advanced control system for operating CDs in a functioning NTP system. This work is a scoping study of the MOOSE STM.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

IDAES-PSE 2.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.0.0 Release Highlights Removal of deprecated features from IDAES v1 Update to Pyomo v6.5 – this required a number of updates to support the new NL solver writer and to address some changes in Pyomo Creation of new testing suite for backward compatibility, model robustness and verification More general implementation of the Helmholtz EoS. This brings some new features like standard property diagrams, choice of mass or mole basis, and new state variable options Standardizing names in Heat Exchanger models (breaking change from v2.0.0a2): Control Volumes named hot_side and cold_side Ports names hot_side_inlet, hot_side_outlet, cold_side_inlet and cold_side_outlet Config Blocks names hot_side_config and cold_side_config Config arguments for user provided names for each side: hot_side_name and cold_side_name. Updating Keras surrogate tool to use v1.1 of OMLT New prototype API for model initialization (idaes.core.initialization) The new API uses "Model Initializer" objects instead of class methods, allowing for the definition of multiple initialization routines for a single model A number of common, model agnostic initialization routines have also been defined, including initialization from data, block-decomposition and a general hierarchical approach equivalent to the existing method for common unit models New metadata for thermophysical properties – valid_range This can be used to record the range of values over which a property value can be trusted, such as the range of experimental data used to regress parameters A number of new utility functions have been added to check for properties with values outside the valid range and to set bounds based on this metadata Updated construction of balance expressions in Control Volumes to remove unneeded terms In the past, unneeded terms were added as a constant 0 term, however they will now be dropped entirely from the expression This was necessary due to more strict unit checking in the new Pyomo solver writer which no longer ignores 0 terms Updates to metadata for thermophysical properties to better define known properties and units of measurement This results in more strict enforcement of standard naming for thermophysical and reaction properties Users can still define custom properties, but these must be done explicitly using the define_custom_properties() method instead of being implicitly created by add_property() Updated convergence tester utility tool to support definition of benchmark files (JSON format) and comparison of performance to benchmarks Set default iteration limit for IPOPT in IDAES config to 200 iterations Update scaling of example models to work with new Pyomo NL solver writer Improve testing of extensions and examples infrastructure to avoid need for downloading files Updated distillation column to centralize common functionality and remove a number of Pyomo warnings

IDAES↗

Combustion energy frontier research center (CEFRC) final report (August 1, 2009 – July 31, 2016)

The Combustion Energy Frontier Research Center (CEFRC) was established to tackle the single overarching grand challenge of energy sustainability, energy security and global warming: to develop a “validated, predictive, multi-scale, combustion modeling capability to optimize the design and operation of evolving fuels in advanced engines for transportation applications,” as identified in the DOE report on “Basic Energy Needs for Clean and Efficient Combustion of 21st Century Transportation Fuels”. The challenge is particularly daunting since energy conversion efficiencies and exhaust emissions are governed by coupled chemical and transport processes at multiple length scales ranging from electron excitation to molecular rearrangements to nanoscale particulate formation to turbulent fuel/air mixing. To tackle this challenge, the CEFRC assembled a world-class team of 15 principal investigators, with the objectives to: 1) develop and test theoretical models to predict elementary reaction rates, molecule thermalization rates, chemical bond dissociation energies, and nonequilibrium transport properties using quantum chemistry calculations that account for strong electron correlation and multiple electronic potential energy surfaces; 2) develop automated kinetic mechanism generation, reduction, and error control methods for predicting alternative fuel including biofuel oxidation, fuel droplet decomposition, and NOx and particulate formation; 3) validate and improve the predictions of these models by measuring ignition delay times, species profiles, flame structures, burning limits, turbulence-kinetic coupling, and NOx and soot emissions at high-pressures and near-limit conditions, by using advanced experimental diagnostic techniques including multiple laser techniques, molecular beam sampling and synchrotron photoionization, and by conducting the measurements in high-pressure shock tubes, jet-stirred and flow reactors, flame bombs, counterflow flames, and advanced-design rapid compression ignition instruments; and 4) develop a suite of validated petascale high-fidelity simulation and modeling capabilities to understand and predict chemistry-turbulence-radiation coupling for new fuels in new regimes, including the high pressure, low-temperature combustion in advanced engine and turbine designs, and 5) establish a knowledge highway between researchers and engineers in academia, national laboratories, and industry to facilitate the dissemination and exchange of knowledge on national and international levels, and enrich the talent pool and capabilities of the next generation of combustion scientists and engineers. The technical activities of the CEFRC were conducted through three Disciplinary Working Groups – Chemistry Theory, Experiment and Mechanism, and Reacting Flows, which coordinated the Center’s research on the development of combustion chemistry of Foundation Fuels (C0–C4 hydrocarbons), Alcohols, and Biodiesel through three corresponding Mechanism Thrust Groups. Such a two-dimensional coordinated and tightly interwoven research structure has been proven to be highly effective in assuring the interplay between the developments of the fundamentals of combustion science and the utilization of the various categories of fuels. The Center has accomplished the above goals over the five year period (August 1, 2009 – July 31, 2014) with appropriated funding, followed by two additional no-cost-extension (NCE) years. The research results are documented in 230 journal publications, with six legacy review papers on the study of combustion chemistry using shock tubes, flow reactors, rapid compression machines, and flames, on uncertainty quantification, and on theoretical reaction dynamics and chemical modeling of combustion. A robust outreach program complemented these PI-led research activities, consisting of: 1) a roving post-doc program comprised of a corps of Center-appointed, co- or multi-sponsored post-doctoral fellows with rotating assignments to conduct seed projects initiated by at least two PIs, in residence with these sponsoring PIs, to rapidly pursue new and high-risk, high-payoff interdisciplinary ideas; 2) an annual summer school on combustion heavily attended (~200) by senior graduate students and practicing researchers covering advanced topics on chemical kinetics, fluid mechanics, turbulent combustion, engine combustion, new technologies, etc.; 3) a robust open web-site providing Center and community information as well as the lecture videos and notes of the summer school; and 4) widely distributed biannual newsletters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Scale up, Field testing, and Optimization of Nontoxic, Durable, Economical Coatings for Control of Biofouling and Corrosion (Abstract Only)

The objective of this project is the technical maturation and demonstration of a durable, economical, and nontoxic coating, Superhydrophobic Lubricant Infused Composite (SLIC), that will prevent fouling organisms from growing on marine and hydrokinetic (MHK) structures and prevent invasive mussels from growing on hydropower structures. SLIC technology was developed and patented by PNNL. It combines multiple antifouling mechanisms to provide excellent antifouling performance, durability, and low hydrodynamic drag without using toxic materials. Advanced proof-of-concept testing and demonstrations completed during a Phase 1 TCF project attracted industry interest and partnerships for this Phase 2 effort focused on maturation of a commercial product. Specific tasks and tests will shift the development emphasis to optimizing formulations, validating antifouling performance to address specific application needs, explore compatibility with other paint systems, develop a product with useful shelf life (in can), and determine curing times and effective applications methodology. Phase 2 efforts will focus upon technology transfer and commercialization of the technology with the industrial team. Industrial partners now include a coatings development specialist (Lorama), hydrophobic material manufacturer and paint developer (Dry Surface Technologies), nontoxic biodegradable lubricants manufacturer (BioBlend), and aquatic applications specialists (Prometheus Innovations, River Connectivity Systems). Engagement with the MHK device developers, the PNNL Marine and Coastal Research Laboratory (MCRL) test site in Sequim WA, Bureau of Reclamation, and Taylor Shellfish throughout the project will provide topical expertise and field test sites that will deliver crucial real-world performance data. Through this Phase 2 effort, SLIC will transition from a Technical Readiness Level (TRL) 5 to TRL 6 and long-term performance data will be acquired through demonstrations. The field test data will allow optimization of SLIC formulation to enhance performance (e.g., durability) and packaging, which are key de-risking activities for technology transfer and ultimately to the production of a viable commercial product.

13 HYDRO ENERGY↗

WE-AB-209-09: Optimization of Rotational Arc Station Parameter Optimized Radiation Therapy

Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of improving VMAT in both plan quality and delivery efficiency. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based Proximal Operator Graph Solver (POGS) within seconds. Apertures with zero or low weight were thrown out. To avoid being trapped in a local minimum, a stochastic gradient descent method was employed which also greatly increased the convergence rate of the objective function. The above procedure repeated until the plan could not be improved any further. A weighting factor associated with the total plan MU also indirectly controlled the complexities of aperture shapes. The number of apertures for VMAT and SPORT was confined to 180. The SPORT allowed the coexistence of multiple apertures in a single SP. The optimization technique was assessed by using three clinical cases (prostate, H&N and brain). Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. Prostate case: the volume of the 50% prescription dose was decreased by 22% for the rectum. H&N case: SPORT improved the mean dose for the left and right parotids by 15% each. Brain case: the doses to the eyes, chiasm and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the H&N case. Conclusion: The superior dosimetric quality and delivery efficiency presented here indicates that SPORT is an intriguing alternative treatment modality.

60 APPLIED LIFE SCIENCES↗

ForceFinder

SAND2025-11750O ForceFinder extends the Structural Dynamics Python Libraries (SDynPy) with comprehensive tools for inverse source estimation (ISE) tasks via frequency response function (FRF) matrix inversion. The software is designed for transfer path analysis and multiple-input/multiple-output (MIMO) vibration control problems. It allows users to estimate sources through various algorithms, from the basic Moore-Penrose pseudo-inverse to statistical learning methods such as Tikhonov regularization via an L-curve and elastic net regularization via an information criterion. ForceFinder uses an object-oriented framework, where all components of the ISE problem—such as FRFs, responses, and transformations—are stored in a "SourcePathReceiver" object. This software can be applied to any noise and vibration problem. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Carter, Steven [Sandia National Lab. (SNL-CA), Liv↗

Innovative Dual Fuel Aftermarket Emissions Solution

The objective of this project was to develop an advanced emission control system for Class 7 and 8 heavy-duty dual-fuel vehicles that eliminate or mitigates the negative effects of currently used diesel particulate filters (DPF) and selective catalytic reduction (SCR) emissions-treatment systems. The project combined multiple technologies that worked together to increase engine efficiency and reduce most emissions from the combustion process.

42 ENGINEERING↗

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictates the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.

97 MATHEMATICS AND COMPUTING↗

Automated Glovebox Work-cell Design - 18370

Los Alamos National Laboratory (LANL) is the primary plutonium science and manufacturing facility in the United States supporting multiple national security programs. It is responsible for completing a high variety of small-batch manufacturing tasks requiring the handling and precision machining of Special Nuclear Materials (SNM). Given the myriad of tasks that must be completed in a limited workspace, LANL intends to utilize flexible, multi-use robotic work-cells capable of completing a variety of mission critical tasks in a single glovebox with no re-tooling needed between batch jobs. This approach would allow LANL more flexibility in its production schedule and to meet its future production and research objectives. In this paper, we present a system that integrates multiple sensors and other manufacturing peripherals into existing glovebox infrastructure. Currently, a technician can place an object in the work area where vision sensors and supervisory software identify the object and its pose and automatically determine which manufacturing task to complete. Pose uncertainty is addressed in real-time by the task planner, eliminating the need for fixtures. Grasps are validated using pressure sensors, payload sensors, and grasp quality metrics to ensure that objects are not dropped or damaged during manipulation. The robot, sensors, and peripherals are controlled using open-source software built utilizing ROS (Robot Operating System), which minimizes redevelopment and allows for re-use and extensibility. Established capabilities support vision, collision-free path planning, and more, minimizing development time. For this effort, particular attention was given to the integration of general peripheral devices (drill, chuck, etc.), which is critical to efficiently utilizing ROS in manufacturing environments. This integration is achieved with an in-development framework that allows for quick integration of peripherals, including I/O devices and motors. Contact tasks utilize the Generalized Contact Control Framework (GCCF) previously developed at UT Austin. GCCF allows application developers to easily define multiple contact control tasks for a single robot. This paper summarizes the key software components necessary to develop the multi-use work-cell including existing ROS components. UT-developed software for grasp validation, peripheral integration, and contact control is presented in more depth. Finally the glovebox system is demonstrated completing a set of tasks with no fixturing necessary. Primary tasks include surface preparation/ablation, drilling, press-fitting, and sorting, as well as supporting material transfer and inspection tasks. The glovebox work-cell reduces cost, operator dose, ergonomic issues, and time loss due to material transfer between gloveboxes that only support one task. If multiple glovebox work-cells are in use, they have the potential to eliminate bottlenecks and scale production capabilities beyond current limits. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗