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DOE OSTI2022

A Critical Review of Heat Pipe Experiments in Nuclear Energy Applications

This critical review provides heat pipe (HP) experimental data sets that contain pertinent information regarding nuclear technology that may be beneficial to researchers. Heat pipes have been shown to have a tremendously positive impact on nuclear technologies and will continue to become a more prevalent technology as more nuclear reactor concepts embrace this robust technology. Most previous reviews may focus on only a specific HP design or application, and some are backdated. Herein, this critical review extends previous efforts; integrates and summarizes previously reported HP experimental efforts; and provides updates with recently reported results in the literature for HPs in all nuclear-related applications, including space power (thermal radiators, core cooling, and electricity production), microreactors (emergency core cooling, hybrid control rods, and reactor core cooling), and HP involvement in other nuclear-related technologies (spent fuel pool cooling). The two main objectives of this critical review are (1) to facilitate the development of HP codes by outlining some of the existing experimental data sets to validate their codes and directing developers to these efforts and (2) to provide comprehensive information regarding the vast applicability of HPs used in the nuclear industry, including the theory of operation and limitations to supplement researchers in the development of new ideas for potential applications in nuclear-related technologies. The review clearly shows extensive and diverse experimental data sets for HPs developed under diverse testing conditions depending on the available nuclear application for validation purposes. Thus, this critical review is oriented to providing attention to the existing efforts rather than determining gaps in HP research.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark—A Bayesian Inverse UQ-Based Approach for Data Assimilation

The Organisation for Economic Co-operation and Development Working Party on Nuclear Criticality Safety has proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian inverse uncertainty quantification (IUQ) employing scientific machine learning surrogate models as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of generalized linear least squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. Here, when comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that the GLLS predictions failed to replicate the computed response distributions for nonlinear applications, while MOCABA showed near agreement, and IUQ used the computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

Bayesian calibration↗

DOE OSTI2023

Visualizing the NIOSH Pocket Guide: Open-source web application for accessing and exploring the NIOSH Pocket Guide to Chemical Hazards

The NIOSH Pocket Guide to Chemical Hazards is a trusted resource that displays key information for a collection of chemicals commonly encountered in the workplace. Entries contain chemical structures—occupational exposure limit information ranging from limits based on full-shift time-weighted averages to acute limits such as short-term exposure limits and immediately dangerous to life or health values, as well as a variety of other data such as chemical-physical properties and symptoms of exposure. The NIOSH Pocket Guide (NPG) is available as a printed, hardcopy book, a PDF version, an electronic database, and a downloadable application for mobile phones. All formats of the NIOSH Pocket Guide allow users to access the data for each chemical separately, however, the guide does not support data analytics or visualization across chemicals. This project reformatted existing data in the NPG to make it searchable and compatible with exploration and analysis using a web application. The resulting application allows users to investigate the relationships between occupational exposure limits, the range and distribution of occupational exposure limits, and the specialized sorting of chemicals by health endpoint or to summarize information of particular interest. These tasks would have previously required manual extraction of the data and analysis. The usability of this application was evaluated among industrial hygienists and researchers and while the existing application seems most relevant to researchers, the open-source code and data are amenable to modification by users to increase customization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A review of non-cognitive applications for neuromorphic computing

Abstract Though neuromorphic computers have typically targeted applications in machine learning and neuroscience (‘cognitive’ applications), they have many computational characteristics that are attractive for a wide variety of computational problems. In this work, we review the current state-of-the-art for non-cognitive applications on neuromorphic computers, including simple computational kernels for composition, graph algorithms, constrained optimization, and signal processing. We discuss the advantages of using neuromorphic computers for these different applications, as well as the challenges that still remain. The ultimate goal of this work is to bring awareness to this class of problems for neuromorphic systems to the broader community, particularly to encourage further work in this area and to make sure that these applications are considered in the design of future neuromorphic systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

The use of haptic interfaces and web services in crystallography: an application for a `screen to beam' interface

Haptic interfaces have become common in consumer electronics. They enable easy interaction and information entry without the use of a mouse or keyboard. Our work illustrates the application of a haptic interface to crystallization screening in order to provide a natural means for visualizing and selecting results. By linking this to a cloud-based database and web-based application program interface, the same application shifts the approach from `point and click' to `touch and share', where results can be selected, annotated and discussed collaboratively. Furthermore, in the crystallographic application, given a suitable crystallization plate, beamline and robotic end effector, the resulting information can be used to close the loop between screening and X-ray analysis, allowing a direct and efficient `screen to beam' approach. The application is not limited to the area of crystallization screening; `touch and share' can be used by any information-rich scientific analysis and geographically distributed collaboration.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2021

Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs

Computational bioinformatics and biomedical applications frequently contain heterogeneously sized units of work or tasks, for instance due to variability in the sizes of biological sequences and molecules. Variable-sized workloads lead to load imbalances in parallel implementations which detract from efficiency and performance. Many modern computing resources now have multiple graphics processing units(GPUs) per computer for acceleration. These multiple GPU resources need to be used efficiently through balancing of workloads across the GPUs. OpenMP is a portable directive-based parallel programming API used ubiquitously in bioscience applications to program CPUs; recently, the use of OpenMP directives for GPU acceleration has become possible. Here, motivated by experiences with imbalanced loads in GPU-accelerated bioinformatics applications, we address the load balancing problem using OpenMP task-to-GPU scheduling combined with OpenMP GPU offloading for multiply heterogeneous workloads – loads with both variable input sizes, and simultaneously, variable convergence rates for algorithms with a stochastic component – scheduled across multiple GPUs. We aim to develop strategies which are both easy to use and have lower overheads, and may be incorporated incrementally in existing programs which already make use of OpenMP for CPU-based threading in order to make use of multi-GPU computers. We test different combinations of input size variability and convergence rate variability, and characterize the effects of these different scenarios on the performance of scheduling strategies across multiple GPUs with OpenMP. We present several dynamic scheduling solutions for different parallel patterns, explore optimizations, and provide publicly available example computational kernels to make these strategies easy to use in programs. This work will enable application developers to efficiently and easily use multiple GPUs for imbalanced workloads found in bioinformatics and biomedical applications.

Thavappiragasam, Mathialakan↗

DOE OSTI2019

Application of Rank-Weight Methods to Blockchain Cybersecurity Vulnerability Assessment Framework

Cybersecurity vulnerability assessment tools, frameworks, and methodologies are used to understand the cybersecurity maturity of a system or a facility. However, these tools are strictly developed based on standards defined by organizations such as the National Institute of Standards and Technology (NIST) and the U.S. Department of Energy; the majority of these tools and frameworks do not provide a platform to prioritize the requirements to reach a desired cybersecurity maturity. To address that challenge, we have been developing a framework and software application called cybersecurity vulnerability mitigation framework through empirical paradigm (CyFEr). CyFEr treats the problem at hand as a multi-criteria decision analysis (MCDA) problem, which requires that various criteria be weighed relatively. Defining those weights is non-trivial and often leads to subjective decisions leading to undesired complications. To facilitate such a weighting system in CyFEr, we evaluated the application of various rank-weight methods (such as rank sum, reciprocal rank, rank exponent, and rank order centroid). The efficacy of those rank-weight methods was evaluated by applying them and testing against the blockchain cybersecurity framework (BC2F). BC2F was developed using the NIST cybersecurity framework to evaluate the cybersecurity posture of the blockchain nodes and networks in a given blockchain application or use-case. This paper provides 1) technical insights on the application of rank-weight methods to cybersecurity vulnerability assessments, 2) an overview of BC2F, 3) the application of rank-weight methods to BC2F, and 4) a depiction of the integration of the discussed rank-weight methods in CyFEr.

Gourisetti, Sri Nikhil G.↗

DOE OSTI2021

DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications

Coarse-grained reconfigurable arrays (CGRAs) provide higher flexibility than application-specific integrated circuits (ASICs) and higher efficiency than fine-grained reconfigurable devices such as Field Programmable Gate Arrays (FPGAs). However, CGRAs are generally designed to support offloading of a single kernel. While their design, based on communicating functional units, appears to naturally suit streaming applications composed of multiple cooperating kernels, current approaches only statically partition the resources across kernels. However, streaming applications often are data-dependent, leading to variable kernel execution times depending on the input data and impacting the throughput of the entire pipeline if resources are statically allocated. Therefore, in this paper, we discuss the design of DynPaC — a coarse-grained, dynamically, and partially reconfigurable array for data-dependent streaming applications. We discuss the required software and hardware components to manage partial dynamic reconfiguration. We demonstrate that by supporting partial dynamic reconfiguration, we can obtain an average speedup of 1.44X for a representative set of applications w.r.t. static partitioning, with a limited area overhead (6.4% of the entire chip).

Tan, Cheng↗

DOE OSTI2017

Apply or Die: On the Role and Assessment of Application Papers in Visualization

Application-oriented papers provide an important way to invigorate and cross-pollinate the visualization field, but the exact criteria for judging an application paper's merit remain an open question. This article builds on a panel at the 2016 IEEE Visualization Conference entitled "Application Papers: What Are They, and How Should They Be Evaluated?" that sought to gain a better understanding of prevalent views in the visualization community. This article surveys current trends that favor application papers, reviews the benefits and contributions of this paper type, and discusses their assessment in the review process. It concludes with recommendations to ensure that the visualization community is more inclusive to application papers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Fast Demand Forecast of Electric Vehicle Charging Stations for Cell Phone Application

This paper describes the core cellphone application algorithm which has been implemented for the prediction of energy consumption at Electric Vehicle (EV) Charging Stations at UCLA. For this interactive user application, the total time of accessing database, processing the data and making the prediction, needs to be within a few seconds. We analyze four relatively fast Machine Learning based time series prediction algorithms for our prediction engine: Historical Average, kNearest Neighbor, Weighted k-Nearest Neighbor, and Lazy Learning. The Nearest Neighbor algorithm (k Nearest Neighbor with k=1) shows better performance and is selected to be the prediction algorithm implemented for the cellphone application. Two applications have been designed on top of the prediction algorithm: one predicts the expected available energy at the station and the other one predicts the expected charging finishing time. The total time, including accessing the database, data processing, and prediction is about one second for both applications.

Majidpour, Mostafa↗

DOE OSTI2021

An Application for Validation of Power Distribution System Models in an ADMS Environment

An accurate model of a power distribution system is the foundation for model-based applications that ensure efficient and reliable grid operation in an advanced distribution management system (ADMS) environment. However, these models are error-prone and comprehensive model validation is challenging due to lack of standards-based systems, data originating from disparate databases and other sources, and the constantly evolving nature of modern power distribution systems. In this paper, a novel framework for comprehensive model validation is described. The proposed application, the Model Validator, ensures that a model is both consistent and feasible by validating the derivative static and operational network model. A modular architecture for the application has been implemented and integrated with an open-source standards-based platform for ADMS application development, GridAPPS-D, allowing new validation capability to be added with minimal time and effort. The Model Validator application is demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test cases over three validation scenarios.

Poudel, Shiva↗

DOE OSTI2016

Pellet Injection Technology and Its Applications on ITER

Cryogenic pellet injectors for use in fusion research have been under development at Oak Ridge National Laboratory for over 30 years. The original application of the technology was to add fuel to magnetically confined plasmas to replace D-T ions that are consumed in the fusion reactions or lost due to transport out of the confining magnetic fields. This application is still the primary use for pellet injection and is planned for implementation on the ITER burning plasma experiment. More recently, there have been additional applications for the injection of cryogenic pellets in the areas of disruption and edge-localized mode mitigation. Injectors for these applications are also being implemented for ITER, which require refinements of the technology for production and shattering of very large pellets and production of very small high repetition rate pellets, respectively. Details of these applications and injection system designs are presented.

Baylor, Larry R.↗

DOE OSTI2022

Superconducting Shuttle-Flux Shift Register for Race Logic and Its Applications

Here this paper presents a superconducting, magnetically-coupled, shuttle-flux shift register (SF-SR) that stores single flux quantum (SFQ) pulses. This shift register has a DC bias operating margin of ±34% at 10 GHz, with a power dissipation of 3.6 μW and 38% fewer Josephson junctions (JJs) when scaled up to multiple stages compared to a data flip-flop (DFF) based shift register. The clock input is inductively coupled and is independent from the data input. We then present three applications for our SF-SR. In the first application, we add two non-destructive readout (NDRO) cells to construct a buffer that temporarily stores the temporal information of a series of race logic (RL) pulses. The second application is a pseudo-random number generator based on a linear function shift register (LFSR). The third application is N parallel SF-SRs that can act similar to a deserializer or instead can emulate a single SF-SR of N times higher clock frequency. These three applications motivate deep shift registers with many shifting intervals, which our SF-SR can implement with fewer JJs and lower power consumption compared to DFF-based shift registers.

42 ENGINEERING↗

DOE OSTI2020

Evaluation and Demonstration of Blockchain Applicability Framework

Blockchain technology has been gaining great interest from a variety of industry sectors, including financial, food processing, and power and energy markets. Realizing the strength of blockchain technology beyond the successful application in the cryptocurrency arena, researchers have been evaluating and using blockchain for applications such as supply chain management, transactive industry (both financial and energy), system integrity, device cybersecurity, identity management, and much more. One of the unique elements of the blockchain technology that made it such a captivating technology to researchers is its plethora of features. Some of the features include smart contracts, cryptocurrency and tokenizing, immutable distributed ledger, cryptographic hashing, and digital signature. In addition, there are multiple types of blockchains, such as permissioned/private and permissionless/public, and various consensus models, such as proof-of-work, proof-of-authority, proof-of-burn, and proof-of-stake. Therefore, it is often non-trivial to determine if an application requires a blockchain. If so, what kind of blockchain and consensus is most appropriate? This paper discusses the blockchain applicability framework (BAF), which was specifically designed with the purpose to answer those questions. BAF is divided into five domains, 18 subdomains, and about 100 controls. It is designed to ingest detailed user requirements to perform a weighted evaluation that is built on mathematical constructs to determine the ideal combination of blockchain that is appropriate for an application. Along with the core logical formulation of BAF, this paper depicts the efficacy of BAF through two use cases

Gourisetti, Sri Nikhil G.↗

DOE OSTI2018

Profiling and Predicting Application Performance on the Cloud

Cloud providers continue to expand and diversify their collection of leasable resources to meet the needs of an increasingly wide range of applications. While this flexibility is a key benefit of the cloud, it also creates a complex landscape in which users are faced with many resource choices for a given application. Suboptimal selections can both degrade performance and increase costs. Given the rapidly evolving pool of resources, it is infeasible for users alone to select instance types; instead, automated methods are needed to simplify and guide resource provisioning. Here we present a method for the automatic prediction of application performance on arbitrary cloud instances. We combine offline and online profiling approaches, using historical data gathered from non-cloud environments and targeted profiling runs on cloud environments to create a composite application model that can predict run times on a given cloud instance type for a given input data size. We demonstrate average error of 17.2% across nine applications used in production bioinformatics workflows. Finally, we evaluate an experiment design approach to explore the trade-off between the cost of profiling and the accuracy of our models. Using this approach, with no prior knowledge, we show that using 4 selectively chosen experiments we can achieve performance within 30% of a model trained using all instance types.

Cloud profiling↗

DOE OSTI2017

Applicability Analysis of Validation Evidence for Biomedical Computational Models

Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibility of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. In this paper, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. Finally, the proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

SU-E-T-560: Commissioning An HDR Freiburg Flap Applicator for Skin Lesion Treatment

Purpose: Flexible Freiburg flap used with high dose rate afterloaders is easy to cut into any size for any body site and to dwell with a precise source position, conforms to curved skin surface and then to the planned target. However, unlike intracavity or interstitial situations, incomplete scatter environment due to flap applicators exposed to air might lead to dose difference between the delivered and planned. This research is focused on the dose deviation of incomplete scatter versus full scatter. Methods: A 12x12 cm of Freiburg flap applicator was used for the validation. A Nucletron Oncentra Brachy Ver. 4.3 treatment planning system (TPS) was used for treatment planning. However, no heterogeneity correction incorporated into the brachytherap TPS needs to be considered. A Philips Brilliance CT Big Bore was employed for CT scan. Radiation was delivered using a Nucletron HDR remote afterloader system. A 10cm bolus was used to cover the flap for obtaining a full scatter. An OSL, ion chamber, and Gafchromic EBT2 film were used for commissioning the flap applicator. Results: The applicator calibration at 5mm depth was performed using an OSL dosimeter. Applicator source dwelling positions with 1D and 2D array exposed to and recorded by Gafchromic EBT2 film showed an agreement within 1mm. 1D array of Freiburg flap exhibited 4.2% cooler in dose with incomplete scatter than full scatter. 2D array showed 7.1% lower in dose for incomplete scatter than full scatter. The deviation was found more than 10% beyond 8cm in depth. Conclusion: Significant dose deviation caused by the incomplete scatter environment was found to be 7.1% at 1cm depth. This deviation was increased with increasing depth. The inaccuracy resulted from the incomplete scatter can be fixed by either placing a bolus on the top of the flap or making the plan at least 7% hotter.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

SU-E-J-207: Effect of Pulse Sequence Parameters On Geometric Distortions Induced by a Titanium Brachytherapy Applicator

Purpose: To investigate the effect of readout bandwidth and voxel size on the appearance of distortion artifacts caused by a titanium brachytherapy applicator. Methods: An acrylic phantom was constructed to rigidly hold a MR conditional, titanium Fletcher-Suit-Delclos-style applicator set (Varian Medical Systems) for imaging on CT (Philips Brilliance) and 1.5T MRI (Siemens Magnetom Aera). Several variants of MRI parameters were tried for 2D T2-weighted turbo spin echo imaging in comparison against the standard clinical protocol with the criteria to keep relative SNR loss less than 20% and imaging time as short as possible. Two 3D sequences were also used for comparison with similar parameters. The applicator tandem was segmented on axial CT images (0.4×0.4×1.5mm {sup 3} resolution) and the CT images were registered to the 3D MR images in Eclipse (Varian). The applicator volume was then overlaid on all MRI sets in 3D-Slicer and distances were measured from the tandem tip to the MRI artifact edge in right/left/superior and anterior/posterior/superior directions from coronal and sagittal 2D acquisitions, respectively, or 3D data reformats. Artifact regions were also manually contoured in coronal/sagittal orientations for area measurements. Results: As would be expected, reductions in voxel size and increases in readout bandwidth reduced artifact size (average max artifact length decreased by 0.95 mm and average max area decrease by 0.27 cm{sup 2}). Interestingly, bandwidth increases yielded reductions in area (0.19 cm{sup 2}) and in distance measurements (1 mm) even with voxel increases, as compared to a standard protocol. This could be useful when high performance protocols are not feasible due to long imaging times. Conclusion: We have characterized artifacts caused by cervical brachytherapy applicator across multiple sequence parameters at 1.5T. Future work will focus on finalizing an optimal protocol that balances artifact reduction with imaging time and then testing this new protocol in patients.

60 APPLIED LIFE SCIENCES↗