Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data intensive computing”

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.

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

At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A Grid Intensity Map-Based Source Model for Monte Carlo Modeling of IMRT Field Irradiation - Paper 5

An accurate source model is important for TPS (Treatment Planning System) dose calculation and verification, especially for IMRT (Intensity Modulated Radiotherapy) irregular and inhomogeneous fields. Monte Carlo simulation is the most accurate way to calculate dose distributions in the heterogeneous media like human bodies. A full radiotherapy modeling generally includes Linac modeling and phantom dose calculation. Full Linac modeling is very time-consuming and requires highly detailed knowledge of the accelerator composition and structure, however, which is very difficult to obtain for commercial interests. Often all relevant parameters are not known with sufficient accuracy, and thus a time-consuming tuning of e.g. the electron beam spot size and energy must be performed. A multiple source model (MSM) regards particles coming from different parts of an accelerator as if they are coming from different virtual sources. MSM uses a set of virtual sources representing the treatment beam (e.g. primary photons, head scatter, electron contamination) by a set of analytic functions or histograms with parameters derived from dosimetric measurements or a full MC simulation. Tillikainen et al built a three sub-source model by matching with measurement data using an automatic process to optimize the free model parameters for a Varian 2100 C/D accelerator. Lin et al have built a convenient five-photon-sub-source model for Varian 2300C 6 MV-X beam based on Monte Carlo simulated Linac for ARTS (Accurate Radiotherapy System). The particle generation of MSM is very fast compared to full Linac simulation, and its sampling efficiency is not limited by the size of the phase space file (PSF). However, generally MSM is generated based on regular field PSF and needs an irregular component to form the beam shape meanwhile apt to bringing error Linac modeling and MSM producing from PSF analysis actually both are multi-freedom optimization process by adjusting several parameters (e.g. electron energy and angular divergence). Linac modeling adjusts its parameters from the beginning of electron hitting target through all components to fit the simulation to the measurement. MSM tunes its PSF-derived parameters by optimizing to minimize the deviations between the simulation and the measurement. Since the full Linac modeling and the MSM model both need to fine tune their parameters to match the simulation to the measurement, and sometimes maybe offsets the real accelerator for its multi-parameter optimization process. So, why not fine tune directly all source model parameters just behind all Linac components to fit the simulation to the measurement? A grid intensity-based surface source model was suggested here, which assumed the particle emitting from the bottom surface of Linac last beam trimmer MLC (Multi Leaf Collimator). The particle emitting position is sampled on the grid intensity map optimized by TPS, and the particle weight is adjusted by its original grid intensity. This source model not only takes advantage of the Monte Carlo method in the heterogeneous media, but also avoids effectively the transportation speed shortcoming of Monte Carlo simulation through Linac components. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-F-J-225: Histology Study of MR Guided Pulsed Focused Ultrasound On Treatment of Prostate Cancer in Vivo

Purpose: Our previous study demonstrated significant tumor growth delay in the mice treated with pulsed high intensity focused ultrasound (pHIFU). The purpose of this study is to understand the cell killing mechanisms of pHIFU. Methods: Prostate cancer cells (LNCaP), were grown orthotopically in 17 nude mice. Tumor-bearing mice were treated using pHIFU with an acoustic power of 25W, pulse width 100msec and 300 pulses in one sonication under MR guidance. Mutiple sonications were used to cover the whole tumor volume. The temperature (less than 40 degree centigrade in the focal spot) was monitored using MR thermometry. Animals were euthanized at pre-determined time points (n=2) after treatment: 0 hours; 6 hrs; 24 hrs; 48 hrs; 4 days and 7 days. Two tumorbearing mice were used as control. Three tumor-bearing mice were treated with radiation (RT, 2 Gy) using 6 MV photon beams. RT treated mice were euthanized at 0 hr, 6 hrs and 24 hrs. The tumors were processed for immunohistochemical (IHC) staining for PARP (a surrogate of apoptosis). A multispectral imaging analysis system was used to quantify the expression of PARP staining. Cell apoptosis was calculated based on the PARP expression level using the DAB analysis software. Results: Our data showed that PARP related apoptosis peaked at 48 hrs and 7 days in pHIFU treated mice, which is comparable to that for the RT group at 24 hrs. The preliminary results from this study were consistent with our previous study on tumor growth delay using pHIFU. Conclusion: Our results demonstrated that non-thermal pHIFU increased apoptotic tumor cell death through the PARP related pathway. MR guided pHIFU may have a great potential as a safe, noninvasive treatment modality for cancer therapy. This treatment modality may synergize with PARP inhibitors to achieve better therapeutic result.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-201-06: Remote Dosimetric Auditing for Clinical Trials Using EPID Dosimetry: A Pilot Study

Purpose: To perform a pilot study for remote dosimetric credentialing of intensity modulated radiation therapy (IMRT) based clinical trials. The study introduces a novel, time efficient and inexpensive dosimetry audit method for multi-center credentialing. The method employs electronic portal imaging device (EPID) to reconstruct delivered dose inside a virtual flat/cylindrical water phantom. Methods: Five centers, including different accelerator types and treatment planning systems (TPS), were asked to download two CT data sets of a Head and Neck (H&N) and Postprostatectomy (P-P) patients to produce benchmark plans. These were then transferred to virtual flat and cylindrical phantom data sets that were also provided. In-air EPID images of the plans were then acquired, and the data sent to the central site for analysis. At the central site, these were converted to DICOM format, all images were used to reconstruct 2D and 3D dose distributions inside respectively the flat and cylindrical phantoms using inhouse EPID to dose conversion software. 2D dose was calculated for individual fields and 3D dose for the combined fields. The results were compared to corresponding TPS doses. Three gamma criteria were used, 3%3mm-3%/2mm–2%/2mm with a 10% dose threshold, to compare the calculated and prescribed dose. Results: All centers had a high pass rate for the criteria of 3%/3 mm. For 2D dose, the average of centers mean pass rate was 99.6% (SD: 0.3%) and 99.8% (SD: 0.3%) for respectively H&N and PP patients. For 3D dose, 3D gamma was used to compare the model dose with TPS combined dose. The mean pass rate was 97.7% (SD: 2.8%) and 98.3% (SD: 1.6%). Conclusion: Successful performance of the method for the pilot centers establishes the method for dosimetric multi-center credentialing. The results are promising and show a high level of gamma agreement and, the procedure is efficient, consistent and inexpensive. Funding has been provided from Department of Radiation Oncology, TROG Cancer Research and the University of Newcastle. Narges Miri is a recipient of a University of Newcastle postgraduate scholarship.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A Plug-Loads Game Changer: Computer Gaming Energy Efficiency without Performance Compromise

Two-thirds of Americans play computer games. Although among the most complex and energy intensive plug loads, gaming has been largely overlooked in energy research and development and policy. Systems used for computer gaming in California consumed 4.1 terawatt-hours/year in 2016 or $700 million in energy bills, with emissions of 1.5 million tons carbon dioxide equivalent allocated 66 percent to consoles, 31 percent to desktop personal computers, 3 percent to laptops, and less than 1 percent to emerging media streaming devices. Key findings include: • Aggregate energy demand places gaming among the top plug loads in California, with gaming representing one-fifth of the state’s total miscellaneous residential energy use. • Market structure changes could substantially affect statewide energy use; energy demand could rise by 114 percent by 2021 under intensified desktop gaming, or fall by 24 percent given a major shift towards consoles coupled with energy efficiency gains. • Unit energy consumption is remarkably varied across gaming platform types: across 26 systems tested, client-side electricity use ranged from 5 to more than 1,200 kWh per year, reflecting equipment choice and usage patterns. • Some emerging technologies and activities are driving energy demand higher, including processor overclocking, cloud-based gaming, higher-resolution connected displays, and virtual reality gaming. • User behavior influences gaming energy use more than technology choice; duty cycle and game choice are particularly strong drivers of demand. • Energy efficiency opportunities are substantial, about 50 percent on a per-system basis for personal computers and 40 percent for consoles if past rates of improvement continue. While simultaneously quantifying efficiency and gaming performance is problematic, evidence suggests that efficiency can be improved while maintaining or improving user experience. Familiar energy policy strategies can help manage gaming energy demand, although mandatory system-level standards are not promising (component-level measures may be).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

TU-H-BRC-01: A New Fabrication Method for Secondary Skin Collimation Using 3D Scanner and 3D Printer

Purpose: Using secondary skin collimation (SSC) to protect the critical organ surrounding the tumors is always desirable for electron and/or ortho-voltage treatments. However, the time-consuming and labor-intensive fabrication processes of current method (manually fabricate the lead mask) restrict the general use of SSC. The aim of this study is to develop a new SSC fabrication method using 3D scanning and 3D printing technologies in order to largely decrease the human labor involvement and fabrication time, also improve the fabrication accuracy. Methods: First, the patient surface was scanned with a 3D scanner (Structure Sensor, Occipital, CO). The raw scan data was subsequently transferred to a 3D modeling software (Rhinoceros, Ver. 5.0, McNeel North America, Seattle, WA). The tumor contour was then digitized and shielding region was determined by clinicians in the same software. The corresponding SCC conformed to the skin surface was then automatically generated by the software with the proper shielding thickness. The shell of the SCC (with hollow inside) was consequently printed by a 3D printer (Lulzbot TAZ, Aleph Objects, CO) using plastic material. Finally, the hollow mold of SCC was filled up with a melted cerrobend alloy. Once the cerrobend alloy cooled down, the fabrication of SCC was accomplished. Results: The results indicated the proposed method can achieve a much shorter time on making a SCC compared with tradition fabrication method. The processes of making a skin contour model for patients have been eliminated with the new method. SCC created by the new method possessed better accuracy and better conformality to patient’s skin contours. Conclusion: In this study, we have demonstrated a new method for the SCC fabrication. It is anticipated that our method can be an alternative way to replace conventional manual-based methods for electron and/or ortho-voltage SCC fabrication. This research was supported by the Global Ph.D. Fellowship Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant No. 2015H1A2A1034071), Republic of Korea.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

AI-Ready Control System for the Fermilab Accelerator Complex

Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. We describe the requirements and infrastructure necessary to support routine use of artificial intelligence and machine learning (AI/ML) in the accelerator control system. Three capabilities are identified: a machine learning operations (MLOps) framework standardizing the lifecycle of AI/ML automation from data management through deployment and monitoring; a data quality framework defining and enforcing standards required to build trustworthy AI/ML applications; and workflow integration with large language models to assist physicists, engineers, and operators with information retrieval, code development, and routine analysis. Use cases spanning beam diagnostics, beam control, and support system automation illustrate the technical requirements across the complex.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Scalable 3D reconstruction for X-ray single particle imaging with online machine learning

X-ray free-electron lasers offer unique capabilities for measuring the structure and dynamics of biomolecules, helping us understand the basic building blocks of life. Notably, high-repetition-rate free-electron lasers enable single particle imaging, where individual, weakly scattering biomolecules are imaged under near-physiological conditions with the opportunity to access fleeting states that cannot be captured in cryogenic or crystallized conditions. Existing X-ray single particle reconstruction algorithms, which estimate the particle orientation for each image independently, are slow and memory-intensive when handling the massive datasets generated by emerging free-electron lasers. Here, we introduce X-RAI (X-Ray single particle imaging with Amortized Inference), an online reconstruction framework that estimates the structure of 3D macromolecules from large X-ray single particle datasets. X-RAI consists of a convolutional encoder, which amortizes pose estimation over large datasets, as well as a physics-based decoder, which employs an implicit neural representation to enable high-quality 3D reconstruction in an end-to-end, self-supervised manner. We demonstrate that X-RAI achieves state-of-the-art performance for small-scale datasets in simulation and challenging experimental settings and demonstrate its unprecedented ability to process large datasets containing millions of diffraction images in an online fashion. These abilities signify a paradigm shift in X-ray single particle imaging towards real-time reconstruction.

Computer science↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-P-55: The Reaserch of Cervical Cancer Delivered with Constant Dose Rate and Gantry Speed Arc Therapy(CDR-CAS-IMAT) On Conventional Linac

Purpose: Postoperative cervical cancer patients with large target volume and the target shape is concave, treatmented with static intensity-modulated radiotherapy (IMRT) is time consuming. The purpose of this study is to investigate using constant dose rate and gantry speed arc therapy(CDR-CAS-IMAT) on conventional linear accelrator, by comparing with the IMRT technology to evaluate the performance of CDR-CAS-IMAT on postoperative cervical cancer patients. Methods: 18 cervical cancer patients treated with IMRT on Varian 23IX were replanted using CDR-CAS-IMAT. The plans were generated on Oncentra v4.1 planning system, PTV was prescribed to 50.4 Gy in 28 fractions. Plans were evaluated based on the ability to meet the dose volume histogram. The homogeneity index (HI), conformity index (CI) of target volume, the dose of organs at risk, radiation delivery time and monitor units were also compared. SPSS 19.0 software paired T-test analysis was carried out on the two sets of data. Results: Compared with the IMRT plans PTV’s CI (t= 3.85, P =0.001), CTV’s CI, HI, D90, D95, D98, V95, V98, V100 (t=4.21, −3.18, 2.13, 4.65, 7.79, 2.29, 6.00, 2.13, p=0.001, 0.005, 0.049, 0.000, 0.000, 0.035, 0.000, 0.049), and cord D2 and rectum V40 (t=−2.65, −2.47, p= P =0.017, 0.025), and treatment time and MU (t=−36.0, −6.26, P =0.000, 0.000) were better than that of IMRT group. But the IMRT plans in terms of decreasing bladder V50, bowel V30 (t=2.14, 3.00, P =0.048, 0.008) and low dose irradiation volume were superior to that of CDR-CAS-IMAT plans. There were no significant differences in other statistical index. Conclusion: Cervical cancer patients with CDR-CAS-IMAT on Varian Clinical 23IX can get equivalent or superior dose distribution compared with the IMRT technology. IMAT have much less treatment time and MU can reduce the uncertainty factor and patient discomfort in treatment. This work was supported by the Medical Science Foundation of the health department of Hebei Province (No. 20130253)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data

Commercial trucks are essential elements of the nation's supply chain system. Meanwhile, intensive truck movements contribute significantly to system externalities, such as energy use and air pollution. However, collecting detailed fleet composition and distribution of operational patterns remains a barrier to accurately accounting for these impacts. The recently released 2021 US Vehicle Inventory and Use Survey (US VIUS) fills a critical gap in understanding commercial truck fleet distributions, their operations, and business constraints at the national scale. This study aims to understand the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and calibrate the fleet inputs in regulatory emission models to assess the potential emission implications of the VIUS-derived fleet composition. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to improve fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The study also investigates potential emission reduction benefits under various forecasted fleet electrification scenarios. The energy consumption and critical air pollutant rates by vehicle types are compared between MOVES4 and US VIUS fleets for both current and future scenarios to provide insights into the latest U.S. commercial vehicle fleet characteristics and their implications on energy and emissions. This study helps policymakers and practitioners advance the commercial fleet generation for emission models. It also deepens the understanding of the emission reduction potential of the commercial fleet under various fleet projections.

2021 US VIUS↗
DOE OSTI2018

Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Report of the Second ARTMIP Workshop

Atmospheric rivers (ARs) have for the last decade been broadly recognized for their global and regional significance in mediating energy and water cycles. As a distinct large-scale circulation feature, ARs can be characterized by long, narrow bands of atmospheric moisture transport from the tropics to higher latitudes. They are both an important source of water supply to coastal regions as well as a hazard because of their predisposition to increase flood risk. However, predicting ARs poses a significant challenge to the scientific community, as they exhibit large variability from subseasonal-to-interannual time scales. On multi-decadal and longer time scales, it is unclear how the frequency and intensity of ARs will change with a warming climate. Hence ARs play a significant role in understanding predictability of water cycle variability and extremes as well as becoming a factor in assessing risks to future infrastructures. There is a large body of literature that has explored ARs from both global and regional perspectives and from timescales spanning hourly to centennial. Despite significant progress in understanding ARs, significant gaps remain, e.g., in characterizing the dynamical and thermodynamical processes associated with ARs, improving predictions of ARs at weather and subseasonal-to-seasonal timescales, and understanding and quantifying the impacts of ARs on the design and management of built infrastructures. Furthermore, the consensus definition of ARs remains essentially qualitative, and investigators have had to rely on heuristic definitions of ARs for quantitative studies. In the First Atmospheric River Tracking Method Intercomparison Project (ARTMIP) workshop held in May 2017, it was recognized that (1) there are many heuristic AR tracking algorithms employed in the literature, (2) our quantitative—and possibly qualitative— understanding of ARs and their impacts may depend on the details of the algorithm used, (3) no data set yet exists to systematically explore the impact of AR tracking algorithm choice on scientific results, and (4) the broader scientific community therefore lacks any formal guidance on the advantages and disadvantages of different AR tracking methods. The First ARTMIP workshop defined and launched a multi-tiered intercomparison experiment designed to fill this community need. The first tier of ARTMIP was aimed at understanding the impact of AR algorithms on quantitative baseline statistics and characteristics of ARs, and the second tier includes sensitivity studies designed around specific science questions, such as reanalysis uncertainty and influences associated with climate change. The Second ARTMIP workshop was convened on April 23-24, 2018, as a two-day event, and following the completion of Tier 1 of the ARTMIP effort: an experiment in which most existing AR tracking algorithms were run on a standardized data set of reanalyzed weather conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Investigation of realistic PET simulations incorporating tumor patient's specificity using anthropomorphic models: Creation of an oncology database

Purpose: The GATE Monte Carlo simulation toolkit is used for the implementation of realistic PET simulations incorporating tumor heterogeneous activity distributions. The reconstructed patient images include noise from the acquisition process, imaging system's performance restrictions and have limited spatial resolution. For those reasons, the measured intensity cannot be simply introduced in GATE simulations, to reproduce clinical data. Investigation of the heterogeneity distribution within tumors applying partial volume correction (PVC) algorithms was assessed. The purpose of the present study was to create a simulated oncology database based on clinical data with realistic intratumor uptake heterogeneity properties.Methods: PET/CT data of seven oncology patients were used in order to create a realistic tumor database investigating the heterogeneity activity distribution of the simulated tumors. The anthropomorphic models (NURBS based cardiac torso and Zubal phantoms) were adapted to the CT data of each patient, and the activity distribution was extracted from the respective PET data. The patient-specific models were simulated with the Monte Carlo Geant4 application for tomography emission (GATE) in three different levels for each case: (a) using homogeneous activity within the tumor, (b) using heterogeneous activity distribution in every voxel within the tumor as it was extracted from the PET image, and (c) using heterogeneous activity distribution corresponding to the clinical image following PVC. The three different types of simulated data in each case were reconstructed with two iterations and filtered with a 3D Gaussian postfilter, in order to simulate the intratumor heterogeneous uptake. Heterogeneity in all generated images was quantified using textural feature derived parameters in 3D according to the ground truth of the simulation, and compared to clinical measurements. Finally, profiles were plotted in central slices of the tumors, across lines with heterogeneous activity distribution for visual assessment.Results: The accuracy of the simulated database was assessed against the original clinical images. The PVC simulated images matched the clinical ones best. Local, regional, and global features extracted from the PVC simulated images were closest to the clinical measurements, with the exception of the size zone variability and the mean intensity values, where heterogeneous tumors showed better reproducibility. The profiles on PVC simulated tumors after postfiltering seemed to represent the more realistic heterogeneous regions with respect to the clinical reference.Conclusions: In this study, the authors investigated the input activity map heterogeneity in the GATE simulations of tumors with heterogeneous activity distribution. The most realistic heterogeneous tumors were obtained by inserting PVC activity distributions from the clinical image into the activity map of the simulation. Partial volume effect (PVE) can play a crucial role in the quantification of heterogeneity within tumors and have an important impact on applications such as patient follow-up during treatment and assessment of tumor response to therapy. The development of such a database incorporating patient anatomical and functional variability can be used to evaluate new image processing or analysis algorithms, while providing control of the ground truth, which is not available when dealing with clinical datasets. The database includes all images used and generated in this study, as well as the sinograms and the attenuation phantoms for further investigation. It is freely available to the interested reader of the journal at http://www.med.upatras.gr/oncobase/.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Toward machine-learning-assisted PW-class high-repetition-rate experiments with solid targets

We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Evaluating nonlocal heat transport in directly driven chromium spheres using x-ray spectroscopy

We report on experiments investigating heat transport in laser-generated plasmas using directly driven chromium spheres. The spheres are fielded at the OMEGA laser facility and are driven with laser intensities of 5×10 14 Wcm −2 . Plasma conditions in the corona and scattered light are measured experimentally and compared against predictions from two-dimensional (2D) radiation-hydrodynamic simulations using different heat transport models. Spectroscopic analysis of x-ray self-emission is used as an additional diagnostic. X-ray emission is integrated over a large region of the plasma, probing regions that are not observed by localized optical Thomson scattering. In particular, x-ray emission peaks near the plasma critical density, so emission from optically thin lines provides information on plasma conditions where nonlocal transport is most likely to be significant. Three common heat transport models are considered: local transport with flux limiters f = 0.15 and f = 0.03, and the nonlocal Schurtz–Nicolai–Busquet (SNB) model. Consistent with previous work, both the high-flux (f = 0.15) and SNB models show good agreement with experimentally measured plasma conditions in the corona despite overpredicting laser absorption, whereas the low-flux (f = 0.03) model fails to match any experimental data. Conditions inferred from x-ray self-emission line ratios support this conclusion during the period of laser peak power, although synthetic spectra for all models fail to match the experiment during the transient portions of the pulse. For these reasons, the low-flux model is again rejected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

SU-E-J-04: Integration of Interstitial High Intensity Therapeutic Ultrasound Applicators On a Clinical MRI-Guided High Intensity Focused Ultrasound Treatment Planning Software Platform

Purpose: Interstitial high intensity therapeutic ultrasound (HITU) applicators can be used to ablate tissue percutaneously, allowing for minimally-invasive treatment without ionizing radiation [1,2]. The purpose of this study was to evaluate the feasibility and usability of combining multielement interstitial HITU applicators with a clinical magnetic resonance imaging (MRI)-guided focused ultrasound software platform. Methods: The Sonalleve software platform (Philips Healthcare, Vantaa, Finland) combines anatomical MRI for target selection and multi-planar MRI thermometry to provide real-time temperature information. The MRI-compatible interstitial US applicators (Acoustic MedSystems, Savoy, IL, USA) had 1–4 cylindrical US elements, each 1 cm long with either 180° or 360° of active surface. Each applicator (4 Fr diameter, enclosed within a 13 Fr flexible catheter) was inserted into a tissue-mimicking agar-silica phantom. Degassed water was circulated around the transducers for cooling and coupling. Based on the location of the applicator, a virtual transducer overlay was added to the software to assist targeting and to allow automatic thermometry slice placement. The phantom was sonicated at 7 MHz for 5 minutes with 6–8 W of acoustic power for each element. MR thermometry data were collected during and after sonication. Results: Preliminary testing indicated that the applicator location could be identified in the planning images and the transducer locations predicted within 1 mm accuracy using the overlay. Ablation zones (thermal dose ≥ 240 CEM43) for 2 active, adjacent US elements ranged from 18 mm × 24 mm (width × length) to 25 mm × 25 mm for the 6 W and 8 W sonications, respectively. Conclusion: The combination of interstitial HITU applicators and this software platform holds promise for novel approaches in minimally-invasive MRI-guided therapy, especially when bony structures or air-filled cavities may preclude extracorporeal HIFU.[1] Diederich et al. IEEE UFFFC 46.5 (1999): 1218.[2] Chopra et al. PMB 50.21 (2005): 4957. Funding support was provided by Philips Healthcare and in-kind support from Acoustic MedSystems Inc. Ari Partanen is a paid employee of Philips Healthcare. Goutam Ghoshal and Everette Clif Burdette are paid employees of Acoustic MedSystems Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Criticality Accident Alarm System Shielding Benchmark: Integral Experiment Request 498, Critical Engineering Decision 1 Report

This report supports Critical/Subcritical Experiment Decision 1 (CED-1) for Integral Experiment Request (IER) 498, a shielding benchmark produced using the Godiva IV critical assembly at the National Critical Experiments Research Center (NCERC). Shielding benchmarks are datasets collected to provide a comparison for computer models that simulate the effect of shielding on radiation transmission from a source to a detector. The purpose of a CED-1 report is to produce a conceptual design for an integral experiment and to identify the long lead-time items. The design presented in this report favors certain detailed design options such as material selections. However, alternative options can be selected as the project evolves. Dimensions are specified only as needed to evaluate feasibility and performance. Development of Criticality Accident Alarm System (CAAS) shielding benchmarks supports two main programmatic needs. The first need is to improve confidence in models of facilities that house nuclear material handling operations. Better models can support effective CAAS detector placement when criticality may result in dose, and it enables more accurate analysis of criticality accident impacts at various locations in a facility. A key quantity that can be verified is the secondary gamma production caused by neutron interactions with various materials. The second programmatic need supported by shielding benchmarks is the ongoing development of methods being integrated into nuclear simulation codes such as the Monte Carlo N-Particle (MCNP) transport code and the SCALE code system used in efforts funded by the Nuclear Criticality Safety Program (NCSP). Previous work performed under the International Criticality Safety Benchmark Experimental Program (ICSBEP) to produce shielding benchmark data is primarily limited to a set of measurements at the SILENE critical assembly at the Valduc facility in France. The experiment used an open configuration and a burst mode operation, which limited detector options to thermoluminescent dosimeters (TLDs) and activation foils. Because TLDs do not record gamma spectra, it was difficult to verify the gamma energy spectrum from the experiment. In this work, the Godiva IV assembly will be used because it is a fast system capable of producing a wide range of source strengths, including super-prompt critical bursts. The room return for the facility is expected to be substantial and challenging to characterize, so a more closed, shielded experimental configuration is considered. Furthermore, because the physics of radiation transport outside the assembly does not change between the burst mode and the delayed critical mode, it is anticipated that most measurements will be made with the Godiva IV assembly in delayed critical mode, operating within a range that will allow electronic counters to collect accurate data. Scoping calculations concluded that a workable room return shield is comprised of 40 cm of 5% borated polyethylene backed by 7 cm of lead. This configuration was shown to produce a ratio of signal–to–room return of over 100 for up to 2 mean free paths of shield sample material, and over 10 for up to 4 mean free paths of shield sample material, ensuring that useful results can be obtained. With no shielding sample in the room return shield, it was shown that the neutron and gamma spectra do not appreciably change with a change in room size. This scoping calculation does not preclude the use of tungsten powder in a binder, some other effective gamma shielding material, or a hybrid design. Dose rates for various source intensities at an unshielded detector are listed herein to inform detector selection during CED-2, and calibration chains are identified. Preliminary estimates of costs and schedules are outlined but remain to be verified. Values could double or triple as estimates become more accurate and are principally included here to demonstrate feasibility. Preliminary estimates indicate that the apparatus can be installed within a feasible schedule and budget. Two measurements per day are assumed. Producing a shielding benchmark at NCERC using the Godiva IV assembly has been shown to be feasible, with manageable uncertainties and risks. A clear, continuing need for shielding benchmark data remains present, and this report identifies and evaluates a method for creating integrated shielding benchmark datasets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗