Crystal plasticity modeling of 3rd generation multi-phase AHSS with martensitic transformation
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When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modular In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.
Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. The current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques such as X-Ray Computed Tomography (XCT), which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. RTX Technologies Research Center (RTRC) has licensed ORNL’s Peregrine software package – a printer- and camera-agnostic data analytics tool designed specifically for detecting process anomalies using in situ data collected during powder bed printing. The goal of this project was to feed temporally rich, multi-modal sensor data, including visible light, integrated near infrared (NIR), and spatially mapped co-axial melt pool thermal emission data into Peregrine to enable detection of subsurface flaws. XCT data was used as ground truth training data to allow Peregrine’s deep learning algorithms to recognize anomalies in these complex data streams in both test artifacts and industrially relevant geometries. Completion of this program has seen the successful implementation of multi-modal, multi-layer sensor data footprints for training of machine learning models in Peregrine. Flaws detected in XCT data have been successfully detected directly from this in situ data footprint, and initial analyses of the in situ probability-of-detection has been conducted, showing performance levels commensurate with traditional non-destructive evaluation (NDE) methods. The in situ monitoring methodology was then applied to an industrially relevant component that was using post-build NDE, highlighting the utility of the proposed method for hard-to-inspect AM components. As a direct result of this program, two journal manuscripts [1], [2] have been published in Additive Manufacturing, with additional manuscripts planned following program completion.
We present the mathematical derivation, software implementation details, and computational results for a semi-smooth Newton method applied to two inverse problems governed by partial differential equations with bound constraints. The two problems share mathematical structural similarities to density-based topology optimization problems. The semi-smooth Newton method provides a mesh independent solution computation for the two test problems. A key step is that the complementarity part of the necessary optimality conditions are reformulated with the use of a complementarity functionφsuch that the complementarity conditions are satisfied if and only if a zero of a nonsmooth function has been obtained. The modular finite element package MFEM is utilized for the software implementation. In addition we constructed a matrix-free Operator to enable the use of efficient Krylov subspace IterativeSolver of MFEM for the solution of our two target problems.
Existing algorithms for predicting milling chatter have not been widely adopted in industry since they require specialized instruments to measure the stability inputs. This study describes how the machining process for a meter-scale aluminum aerostructure was optimized using a physics-guided Bayesian stability model. The study was performed in collaboration with an industrial partner on production machines to evaluate the practicality of the proposed method under real-world conditions. For each cutting tool, the Bayesian approach automatically selected a small number of cutting tests, which were monitored using a microphone to observe the chatter frequency. The algorithm learned the system dynamics, cutting forces, and stability map from these test results. A novel algorithm for predicting tool bending stress was incorporated into the test selection algorithm to avoid tool breakage. On average, each set of optimized cutting parameters required less than six tests to identify and were 97% more productive than baseline parameters from the cutting tool manufacturer. The machining program was then further optimized using commercial feedrate scheduling software to remove cutting force spikes and reduce air cutting time. Five components were machined using the optimized process. These results demonstrate the potential for physics-guided Bayesian models to improve productivity in industrial settings.
The Kepler spacecraft observes a host of target stars to detect transiting planets. Requiring a 7.1{sigma} detection in three years of data yields over 100,000 detections, many of which are false alarms. After a second cut is made on a robust detection statistic, some 50,000 or more targets still remain. These false alarms waste resources as they propagate through the remainder of the software pipeline and so a method to discriminate against them is crucial in maintaining the desired sensitivity to true events. This paper describes a {chi}{sup 2} test which represents a novel application of an existing formalism developed for false alarm mitigation in searches for gravitational waves. Using this technique, the false alarm rate can be lowered to {approx}5%.
Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.
We have investigated a novel gas/solid contacting configuration for chemical looping combustion (CLC) with potential operating benefits. CLC configurations are typically able to achieve high fuel conversion efficiencies at the expense of high operating costs and low system reliability. The spouted fluid bed (SB) was identified as an improved reactor configuration for CLC, since it typically exhibits high heat transfer rates and offers the ability to use lower gas flows for material movement compared to bubbling beds (BB). Multiphase Flow with Interphase eXchanges (MFIX) software was used to establish a spouted fluid bed reactor design. An experimental setup was built to supplement the model. The experimental setup was also modified for testing under high temperature, reacting conditions (1073–1273 K). The setup was operated in either a spouted fluid bed or a bubbling bed regime to compare the performance attributes of each. Results for the reactor configurations are presented for CLC using a mixture of carbon monoxide and hydrogen as fuel. Compared to the bubbling bed, the spouted fluid bed reactor achieved an equivalent or better fuel conversion at a lower pressure drop over the material bed. The spouted fluid bed design represents a viable configuration to improve gas/solid contacting for efficient fuel conversion, lower energy requirements for material movement and increase operational robustness for CLC. The research laid the groundwork for future research into a multi-phase reacting flow CLC system. The system will be developed from computational fluid dynamic modeling and pilot-scale testing to expedite the development of CLC technologies.
GRAPE is a tool for managing software project workflows for the Git version control system. It provides a suite of tools to simplify and configure branch based development, integration with a project's testing suite, and integration with the Atlassian Stash repository hosting tool.
ZFP is a floating-point compression format gaining traction in high-performance computing applications. A software implementation has demonstrated the ability to reduce data movement across communication channels and to reduce the footprint of floating-point arrays in memory. Nevertheless, any benefit in performance is limited to the spare compute cycles available before reaching bandwidth limitations. A hardware implementation of ZFP has the potential to substantially improve HPC application performance. Hardware compression speedup over software alone on a single CPU core ranges from 15x for 1-D arrays to over 200x for 3-D arrays. The implementation of ZFP is sourced in SystemC to facilitate its evaluation in various architectures. The encode pipeline consists of several modules. Uncompressed blocks of floating-point numbers in IEEE format flow into the pipeline in a stream and a compressed bitstream flows out from the pipeline. The decode pipeline is the inverse of the encode pipeline. A modular design enables formats other than IEEE (such as posits) to be considered with minor adaptations. Best performance will be realized from the hardware ZFP unit when batches of blocks are processed at a time. The implementation supports 1-D, 2- D and 3-D blocks of floating-point numbers. The hardware implementation of ZFP has been validated with the software implementation of ZFP. C++ template parameters are used to specify the bit width of floating-point numbers and the array dimension of the encoder. A test bench program has been created with several test cases, some with continuous data that is ideal for ZFP, and others with extreme cases containing numbers near or at the maximum or minimum values supported by the number format.
Southern Company is an electric utility that is embracing residential microgrids as a platform for distributed energy. The first residential microgrid in the southeastern United States was constructed in Hoover, Alabama, as a testbed for development. To operate the microgrid, we developed an optimization model for unit commitment and economic dispatch. We report the optimization model was implemented in a microgrid central controller and tested under various operational scenarios. Challenges also include developing a pricing algorithm to deliver price forecasts to the residential homes in the microgrid and open-source software restrictions.
This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.
This project demonstrated microwave cracking of ethane with good product conversion and ethylene selectivity, with a short residence time (~0.001 sec). The laboratory scale equipment was designed and built, along with concept designs for larger scale implementation. The system was operated below atmospheric pressures, in the range of 15-55 torr, with argon as a carrier gas. The measured products included hydrogen, methane, acetylene, and ethylene. The results followed similar trends to those predicted by the modeling software SPYRO®, with the exception that the microwave appeared to produce slightly lower amounts of ethylene and methane, although enhanced analytical analysis should reduce the difference. Continued testing will be required to verify these results and quantify the energy consumption of microwave vs. conventional. The microwave cracking process is an attractive option due to the possibility of selectively heating the reaction volume rather than the reactor walls, which may allow novel reactor designs that result in more efficient production of ethylene. Supplemental studies are needed to continue the laboratory testing and refine processing parameters.
We review and develop techniques to determine associations between series of discrete events. The bootstrap, a nonparametric statistical method, allows the determination of the significance of associations with minimal assumptions about the underlying processes. We find the key requirement for this method: one of the series must be widely spaced in time to guarantee the theoretical applicability of the bootstrap. If this condition is met, the calculated significance passes a reasonableness test. We conclude with some potential future extensions and caveats on the applicability of these methods. The techniques presented have been implemented in a Python-based software toolkit.
As nuclear power plants undertake main control room modernization, a challenge is the lack of a clearly defined human factors process to follow. Verification and validation (V&V) as applied in the nuclear power community has tended to involve efforts such as integrated system validation, which comes at the tail end of the design stage. To fill in guidance gaps and create a step-by-step process for control room modernization, we have developed the Guideline for Operational Nuclear Usability and Knowledge Elicitation (GONUKE). This approach builds on best practices in the software industry, which prescribe an iterative user-centered approach featuring multiple cycles of design and evaluation. Nuclear regulatory guidance for control room design emphasizes summative evaluation—which occurs after the design is complete. In the GONUKE approach, evaluation is also performed at the formative stage of design—early in the design cycle using mockups and prototypes for evaluation. The evaluation may involve expert review (e.g., software heuristic evaluation at the formative stage and design verification against human factors standards like NUREG-0700 at the summative stage). The evaluation may also involve user testing (e.g., usability testing at the formative stage and integrated system validation at the summative stage). An additional, often overlooked component of evaluation is knowledge elicitation, which captures operator insights into the system. In this report we outline these evaluation types across design phases that support the overall modernization process. The objective is to provide industry-suitable guidance for steps to be taken in support of the design and evaluation of a new human-machine interface (HMI) in the control room. We suggest the value of early-stage V&V and highlight how this early-stage V&V can help improve the design process for control room modernization. We argue that there is a need to overcome two shortcomings of V&V in current practice—the propensity for late-stage V&V and the use of increasingly complex psychological assessment measures for V&V.
Northern Illinois University in collaboration with Fermi National Accelerator Laboratory (FNAL) and Delhi University has been designing and building a proton CT scanner for applications in proton treatment planning. The Phase II proton CT scanner consists of eight planes of tracking detectors with two X and two Y coordinate measurements both before and after the patient. In addition, a range stack detector consisting of a stack of thin scintillator tiles, arranged in twelve eight-tile frames, is used to determine the water equivalent path length (WEPL) of each track through the patient. The X-Y coordinates and WEPL are required input for image reconstruction software to find the relative (proton) stopping powers (RSP) value of each voxel in the patient and generate a corresponding 3D image. In this Note we describe tests conducted in 2015 at the proton beam at the Central DuPage Hospital in Warrenville, IL, focusing on the range stack calibration procedure and comparisons with the GEANT~4 range stack simulation.
Although analysis methods have advanced significantly in the last two decades, high fidelity multi- physics methods for reactors systems have been under development for only a few years and are not presently mature nor deployed. Furthermore, very few methods provide the ability to simulate rapid transients in three dimensions. Data for validation of advanced time-dependent multi- physics is sparse; at TREAT, historical data were not collected for the purpose of validating three-dimensional methods, let alone multi-physics simulations. Existing data continues to be collected to attempt to simulate the behavior of experiments and calibration transients, but it will be insufficient for the complete validation of analysis methods used for TREAT transient simulations. Hence, a 2018 restart will most likely occur without the direct application of advanced modeling and simulation methods. At present, the current INL modeling and simulation team plans to work with TREAT operations staff in performing reactor simulations with MAMMOTH, in parallel with the software packages currently being used in preparation for core restart (e.g., MCNP5, RELAP5, ABAQUS). The TREAT team has also requested specific measurements to be performed during startup testing, currently scheduled to run from February to August of 2018. These startup measurements will be crucial in validating the new analysis methods in preparation for ultimate application for TREAT operations and experiment design. This document describes the collaboration between modeling and simulation staff and restart, operations, instrumentation and experiment development teams to be able to effectively interact and achieve successful validation work during restart testing.
The objective of the Nuclear Criticality Safety Program (NCSP) Analytical Methods program element is to sustain state-of-the-art radiation transport modeling capabilities and the expertise necessary to develop, maintain, and disseminate the analytical tools and data libraries in a manner that is responsive to the needs of those responsible for developing, implementing, and maintaining criticality safety. To this end, the objective of the AMPX Development and Maintenance Subtask is to ensure that the AMPX cross-section processing system is available to prepare cross-section and covariance libraries that are needed by SCALE and other radiation transport packages to support criticality safety analyses of systems with fissionable material. Moreover, the task ensures that the cross-section processing software is current and up-to-date with the Evaluated Nuclear Data File (ENDF/B) formats and procedures for disseminating evaluated cross-section data provided through new measurement and evaluation work efforts. The AMPX subtask provides for the production of data libraries needed for criticality safety analyses. As such, the task provides the “bridge” between the nuclear data evaluations and the radiation transport software. In the absence of the AMPX cross-section processing task, the ability to maintain and update the SCALE nuclear data libraries (cross-section and covariance data) would be hindered. Therefore, the AMPX Development and Maintenance Subtask ensures that SCALE is up-to-date with the latest cross-section data for supporting criticality safety analyses. This letter report provides a summary of the FY 2015 AMPX development and maintenance activities that have been performed in support of the NCSP. Specifically, the report summarizes the AMPX code system updates and modernization accomplishments that have been made to the software package. Also, the report documents the cross-section library updates that have been made for the SCALE radiation transport package. In addition, the report documents testing activities that have been performed to process available cross-section and covariance data files to ensure the latest ENDF/B data files can be processed properly. This report satisfies the following reporting milestone in the NCSP FY16-20 Five Year Plan: Document AMPX modernization and technical support for SCALE continuous energy (CE), multigroup (MG), and covariance libraries and report status annually to the NCSP Manager (AM3: Q2)