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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Visualizing bleb mass dynamics in single cells using quantitative phase microscopy

Understanding biological responses to directed energy (DE) is critical to ensure the safety of personnel within the Department of Defense. At the Air Force Research Laboratory, we have developed or adapted advanced optical imaging systems that quantify biophysical responses to DE. One notable cellular response to DE exposure is the formation of blebs, or semi-spherical protrusions of the plasma membrane in living cells. In this work, we demonstrate the capacity of quantitative phase imaging (QPI) to both visualize and quantify the formation of membrane blebs following DE exposure. QPI is an interferometric imaging tool that uses optical path length as a label-free contrast mechanism and is sensitive to the non-aqueous mass density, or dry mass, of living cells. Blebs from both CHO-K1 and U937 cells were generated after exposure to a series of 600 ns, 21.2 kV/cm electric pulses. These blebs were visualized in real time, and their dry mass relative to the rest of the cell body was quantified as a function of time. It is our hope that this system will lead to an improved understanding of both DE-induced and apoptotic blebbing.

Steelman, Zachary A.↗
DOE OSTI2021

Review of Design Elements within Power Infrastructure Cyber–Physical Test Beds as Threat Analysis Environments

Cyber–physical systems (CPSs) are an integral part of modern society; thus, enhancing these systems’ reliability and resilience is paramount. Cyber–physical testbeds (CPTs) are a safe way to test and explore the interplay between the cyber and physical domains and to cost-effectively enhance the reliability and resilience of CPSs. Here a review of CPT elements, broken down into physical components (simulators, emulators, and physical hardware), soft components (communication protocols, network timing protocols), and user interfaces (visualization-dashboard design considerations) is presented. Various methods used to validate CPS performance are reviewed and evaluated for potential applications in CPT performance validation. Last, initial simulated results for a CPT design, based on the IEEE 33 bus system, are presented, along with a brief discussion on how model-based testing and fault–injection-based testing (using scaling and ramp-type attacks) may be used to help validate CPT performance.

14 SOLAR ENERGY↗
DOE OSTI2021

Achieving Stable Molybdenum Oxide Cathodes for Aqueous Zinc‐Ion Batteries in Water‐in‐Salt Electrolyte

Abstract Layered MoO 3 represents a promising cathode for aqueous rechargeable Zn‐ion batteries, but the implementation of this material is limited due to the low conductivity and poor structural stability. A 30 m ZnCl 2 water‐in‐salt electrolyte (WISE) is introduced to a MoO 3 nanobelt cathode for the first time, significantly increasing the stability of MoO 3 cathodes compared to those in 3 m ZnSO 4 and 3 m ZnCl 2 . The Zn/MoO 3 cell in WISE unambiguously demonstrate significantly improved rate performance delivering 349, 253, and 222 mAh g −1 at 100, 500, and 1000 mA g −1 , denoting a 12× capacity increase of those achieved in 3 m electrolytes at 1000 mA g −1 . A capacity retention rate of 73% is achieved after (dis)charging at 100 mA g −1 for 100 cycles, and no obvious capacity fading is observed at higher current densities of 500 mA g −1 and 2 A g −1 . Specifically, the data suggest that the drastic fading in 3 m electrolytes can be attributed to the parasitic surface deposits on Zn originated from Mo dissolution and H 2 formation due to Zn corrosion and hydrogen evolution reaction, which are significantly suppressed in the WISE. The direct visualization of these side reactions is achieved for the first time in the Zn‐MoO 3 system, using an in situ optoelectrochemical measurement.

Wang, Lei↗
DOE OSTI2018

Adherens junction-associated pores mediate the intercellular transport of endosomes and cytoplasmic proteins

Highlights: • We demonstrated the presence of AJ-associated pores with MTs traversing through the pores. • Live imaging allows direct visualization of vesicles being transported through the AJ-associated pores. • The dimerized vesicle-kinesin complexes move across AJs into the neighboring cell. • Most epidermal cells form dorsoventral-oriented two-cell syncytia. Intercellular endosomes (IEs) are endocytosed vesicles shuttled through the adherens junctions (AJs) between two neighboring epidermal cells during Drosophila dorsal closure. The cell-to-cell transport of IEs requires DE-cadherin (DE-cad), microtubules (MTs) and kinesin. However, the mechanisms by which IEs can be transported through the AJs are unknown. Here, we demonstrate the presence of AJ-associated pores with MTs traversing through the pores. Live imaging allows direct visualization of IEs being transported through the AJ-associated pores. By using an optogenetic dimerization system, we observe that the dimerized IE-kinesin complexes move across AJs into the neighboring cell. The AJ-associated pores also allow intercellular movement of soluble proteins. Importantly, most epidermal cells form dorsoventral-oriented two-cell syncytia. Together, we present a model in which an AJ-associated pore mediates the intercellular transport of IEs and proteins between two cells in direct contact.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Helium Ion Microscopy with Secondary Ion Mass Spectrometry for Nanoscale Chemical Imaging and Analysis of Polyolefins

To date, chemical imaging of polymers and polymer blends has been primarily accomplished using time-of-flight secondary ion mass spectrometry (ToF-SIMS) to directly visualize the distribution of components in a complex material with spatial resolution ranging from 100 nm to 5 μm. However, in many cases, this resolution falls far short of visualizing interfaces directly. To overcome these limitations, recent work has focused on developing a SIMS detection system based on a helium ion microscope (HIM) enabling chemical imaging with a demonstrated ~14 nm spatial resolution. Here, we utilize HIM-SIMS for differentiation between the olefin-based polymers of polyethylene (PE) and polypropylene (PP). We illustrate both analyses for separating PE and PP using specific mass fragment ratios as well as demonstrate spatially resolved imaging of phase-separated domains within PE. Altogether, we demonstrate the abilities of HIM-SIMS as a multimodal chemical technique for imaging and quantification of polyolefin interfaces, which could be more broadly applied to the analysis of more complex polymeric systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Radiation protection program for early detection of breast cancer in a mammography facility

Mammography is the best tool for early detection of Breast Cancer. In this diagnostic radiology modality it is necessary to establish the criteria to ensure the proper use and operation of the equipment used to obtain mammographic images in order to contribute to the safe use of ionizing radiation. The aim of the work was to implement at FUCAM-AC the radiation protection program which must be established for patients and radiation workers according to Mexican standards [1–4]. To achieve this goal, radiation protection and quality control manuals were elaborated [5]. Furthermore, a quality control program (QCP) in the mammography systems (analog/digital), darkroom included, has been implemented. Daily sensitometry, non-variability of the image quality, visualizing artifacts, revision of the equipment mechanical stability, compression force and analysis of repetition studies are some of the QCP routine tests that must be performed by radiological technicians of this institution as a set of actions to ensure the protection of patients. Image quality and patients dose assessment were performed on 4 analog equipment installed in 2 mobile units. In relation to dose assessment, all equipment passed the acceptance criteria (<3 mGy per projection). The image quality test showed that most images (70%)– presented artifacts. A brief summary of the results of quality control tests applied to the equipment and film processor are presented. To maintain an adequate level of quality and safety at FUCAM-AC is necessary that the proposed radiation protection program in this work is applied.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

New insights on the propagation of pulsed atmospheric plasma streams: From single jet to multi jet arrays

Atmospheric pressure plasma propagation inside long dielectric tubes is analyzed for the first time through nonintrusive and nonperturbative time resolved bi-directional electric field (EF) measurements. This study unveils that plasma propagation occurs in a region where longitudinal EF exists ahead the ionization front position usually revealed from plasma emission with ICCD measurement. The ionization front propagation induces the sudden rise of a radial EF component. Both of these EF components have an amplitude of several kV/cm for helium or neon plasmas and are preserved almost constant along a few tens of cm inside a capillary. All these experimental measurements are in excellent agreement with previous model calculations. The key roles of the voltage pulse polarity and of the target nature on the helium flow patterns when plasma jet is emerging in ambient air are documented from Schlieren visualization. The second part of this work is then dedicated to the development of multi jet systems, using two different setups, based on a single plasma source. Plasma splitting in dielectric tubes drilled with sub millimetric orifices, but also plasma transfer across metallic tubes equipped with such orifices are reported and analyzed from ICCD imaging and time resolved EF measurements. This allows for the design and the feasibility validation of plasma jet arrays but also emphasizes the necessity to account for voltage pulse polarity, target potential status, consecutive helium flow modulation, and electrostatic influence between the produced secondary jets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Microfluidic volumetric flow determination using optical coherence tomography speckle: An autocorrelation approach

Functional modalities of Optical Coherence Tomography (OCT) based on speckle analysis are emerging in the literature. We propose a simple approach to the autocorrelation of OCT signal to enable volumetric flow rate differentiation, based on decorrelation time. Our results show that this technique could distinguish flows separated by 3 μl/min, limited by the acquisition speed of the system. We further perform a B-scan of gradient flow inside a microchannel, enabling the visualization of the drag effect on the walls.

42 ENGINEERING↗
DOE OSTI2013

Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: Automated measurement development for full field digital mammography

Purpose: The Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors are used for standardized mammographic reporting and are assessed visually. This reporting is clinically relevant because breast composition can impact mammographic sensitivity and is a breast cancer risk factor. New techniques are presented and evaluated for generating automated BI-RADS breast composition descriptors using both raw and calibrated full field digital mammography (FFDM) image data.Methods: A matched case-control dataset with FFDM images was used to develop three automated measures for the BI-RADS breast composition descriptors. Histograms of each calibrated mammogram in the percent glandular (pg) representation were processed to create the new BR{sub pg} measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR{sub vc} and BR{sub vr} measures, respectively. These three measures were compared with the radiologist-reported BI-RADS compositions assessments from the patient records. The authors used two optimization strategies with differential evolution to create these measures: method-1 used breast cancer status; and method-2 matched the reported BI-RADS descriptors. Weighted kappa (κ) analysis was used to assess the agreement between the new measures and the reported measures. Each measure's association with breast cancer was evaluated with odds ratios (ORs) adjusted for body mass index, breast area, and menopausal status. ORs were estimated as per unit increase with 95% confidence intervals.Results: The three BI-RADS measures generated by method-1 had κ between 0.25–0.34. These measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.87 (1.34, 2.59) for BR{sub pg}; (b) OR = 1.93 (1.36, 2.74) for BR{sub vc}; and (c) OR = 1.37 (1.05, 1.80) for BR{sub vr}. The measures generated by method-2 had κ between 0.42–0.45. Two of these measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.95 (1.24, 3.09) for BR{sub pg}; (b) OR = 1.42 (0.87, 2.32) for BR{sub vc}; and (c) OR = 2.13 (1.22, 3.72) for BR{sub vr}. The radiologist-reported measures from the patient records showed a similar association, OR = 1.49 (0.99, 2.24), although only borderline statistically significant.Conclusions: A general framework was developed and validated for converting calibrated mammograms and continuous measures of breast density to fully automated approximations for the BI-RADS breast composition descriptors. The techniques are general and suitable for a broad range of clinical and research applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

G-PST Inertia Monitoring Tool [SWR-23-54]

This tool provides interfaces for ingesting real-time unit commitment data (e.g., from a grid operator's control room energy management system) and calculating system inertia estimates based on the H-constant method, before relaying those estimates to customizable visualization or logging outputs.

Stephen, Gordon↗
DOE OSTI2019

Mobility Data and Models Informing Smart Cities

Using emerging data platforms, new mobility technologies, and travel demand models (TDMs), researchers, industry, and communities seek to improve the quality of transportation while maximizing the energy efficiency, equity, and safety of transportation services. As transportation may soon reach over 30% of U.S. energy consumption and with urban areas representing an increasing proportion of the U.S. population (>80% since 2010), a critical need exists to engage in urban data science-informed approaches to enhancing mobility. The objective of this study is to explore and document how aspiring Smart Cities are using data and models to inform mobility and energy initiatives within Smart City programs and in so doing identify gaps in knowledge and processes guiding Smart City mobility investment strategies, programs, projects, and pilots. A primary focus of the Smart Cities studied was the creation of an integrated data sharing environment approach. Most of these systems are being developed in parallel with multiple new data analysis tools, while regional metropolitan planning organizations continue to slowly evolve TDMs to take into account impacts of long-term strategies for emerging mobility technologies and services. Smart City initiatives in the United States have keen interests in leveraging knowledge and research on the mobility benefits and risks of automated, connected, efficient/electric, and shared on-demand mobility services; and understanding the related energy, environmental, economic, and societal impacts of these shifts. The results serve to identify key gaps in data, knowledge, and methods required to advance energy efficient urban mobility innovation, and to enable research and analysis collaboration between Smart Cities and the U.S. Department of Energy's efforts enabling new Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

County Land-Use Regulations for Solar Energy Development in Colorado

We present a survey of county-level policies on ground-mounted solar development across Colorado, including both solar-specific ordinances as well as general land-use code that might be applicable in counties without solar-specific policies. This report provides an accessible reference for stakeholders interested in identifying counties with particular regulations or in analyzing the diversity of regulations across Colorado. We defined a set of search criteria to find information on solar definitions and classifications, permitting processes, and use-specific requirements in each of Colorado's 64 counties. With those criteria, we reviewed relevant ordinances, land-use code, and comprehensive and master plans. If any uncertainties were identified, we contacted county officials for clarification. The findings are categorized and mapped to illustrate the distribution of key policies adopted across Colorado's counties on the following topics: solar definitions, solar siting policy documentation, categorization of PV systems for permitting, 1041 permitting, solar on agricultural land, panel height restrictions, fencing requirements, vegetation management, visual impacts, decommissioning plans, and financial assurance for decommissioning. Additionally, we identify and discuss policies that might impact the deployment of agrivoltaics, a dual land use combining both agriculture and solar on the same land, which might not fit neatly in existing zoning definitions and solar-specific regulations.

14 SOLAR ENERGY↗
DOE OSTI2019

Predicting Metallic Defects in Casting BrA9ZhZL Alloy Tool Electrodes

A method is proposed for modeling the lost-wax casting of tool electrodes by means of fusible BrA9ZhZL copper-based alloy. The functionality of the casting system is analyzed. The heating and cooling of a ceramic mold is taken into account in visualizing the temperature fields. Sections where shrinkage pores may form in the casting are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Big Data Framework with Machine Learning for D and D Applications - 19108

The nuclear industry is experiencing a steady increase in maintenance costs even though plants are maintained under high levels of safety, capability and reliability. Nuclear power plants are expected to run every unit at maximum capacity at all times, efficiently utilizing assets with minimal downtime. Surveillance and maintenance of nuclear decommissioning infrastructure provides lot challenges with respect to maintenance or decommissioning of the buildings. There is a need for a framework to analyze the huge amount of data generated by the sensors on the nuclear reactor components as well as structures, to monitor the conditions of these building over a period of time. Emerging technologies such as big data analytics have become a requirement in the nuclear industry to improve structural health monitoring and diagnostics. FIU will make use of existing mature technologies in the areas of imaging, robotics, big data, and machine learning/deep learning to assess the structural integrity of aging facilities at DOE sites. As these facilities await decommissioning, there is a need to understand the structural health of these structures. Many of these facilities were built over 50 years ago and in some cases these facilities have gone beyond the operational life expectancy. In other cases, the facilities have been placed in a state of 'cold and dark' and they are sitting unused, awaiting decommissioning. Finally, some older facilities are one-of-a-kind operational/production facilities supporting critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may be compromised, so it is imperative that adequate inspections and data collection/analysis be performed on a continuous and ongoing basis. The primary goals of the research include collecting various formats of data such as structured, unstructured and streaming data from the various sensors deployed in buildings, collect videos/pictures from various imaging sources, ingest them using a Hadoop distributed file system and process the data using Spark to perform batch processing and real time analytics. Research and development on various machine learning/deep learning algorithms will also be performed to analyze the heterogeneous data collected from nuclear decommission infrastructure. FIU will design the big data framework to ingest, store and process huge amounts of heterogeneous data collected from many sources and optimize the algorithms to provide insights into the data and predict anomalies observed when compared against baseline conditions. Various modules of this framework will include heterogeneous data sources, message broker, Hadoop distributed file system, Spark for stream and batch processing, machine learning/ deep learning, Cassandra - persistent data store and visualization. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Evaluation of the spline reconstruction technique for PET

Purpose: The spline reconstruction technique (SRT), based on the analytic formula for the inverse Radon transform, has been presented earlier in the literature. In this study, the authors present an improved formulation and numerical implementation of this algorithm and evaluate it in comparison to filtered backprojection (FBP). Methods: The SRT is based on the numerical evaluation of the Hilbert transform of the sinogram via an approximation in terms of “custom made” cubic splines. By restricting reconstruction only within object pixels and by utilizing certain mathematical symmetries, the authors achieve a reconstruction time comparable to that of FBP. The authors have implemented SRT in STIR and have evaluated this technique using simulated data from a clinical positron emission tomography (PET) system, as well as real data obtained from clinical and preclinical PET scanners. For the simulation studies, the authors have simulated sinograms of a point-source and three digital phantoms. Using these sinograms, the authors have created realizations of Poisson noise at five noise levels. In addition to visual comparisons of the reconstructed images, the authors have determined contrast and bias for different regions of the phantoms as a function of noise level. For the real-data studies, sinograms of an{sup 18}F-FDG injected mouse, a NEMA NU 4-2008 image quality phantom, and a Derenzo phantom have been acquired from a commercial PET system. The authors have determined: (a) coefficient of variations (COV) and contrast from the NEMA phantom, (b) contrast for the various sections of the Derenzo phantom, and (c) line profiles for the Derenzo phantom. Furthermore, the authors have acquired sinograms from a whole-body PET scan of an {sup 18}F-FDG injected cancer patient, using the GE Discovery ST PET/CT system. SRT and FBP reconstructions of the thorax have been visually evaluated. Results: The results indicate an improvement in FWHM and FWTM in both simulated and real point-source studies. In all simulated phantoms, the SRT exhibits higher contrast and lower bias than FBP at all noise levels, by increasing the COV in the reconstructed images. Finally, in real studies, whereas the contrast of the cold chambers are similar for both algorithms, the SRT reconstructed images of the NEMA phantom exhibit slightly higher COV values than those of FBP. In the Derenzo phantom, SRT resolves the 2-mm separated holes slightly better than FBP. The small-animal and human reconstructions via SRT exhibit slightly higher resolution and contrast than the FBP reconstructions. Conclusions: The SRT provides images of higher resolution, higher contrast, and lower bias than FBP, by increasing slightly the noise in the reconstructed images. Furthermore, it eliminates streak artifacts outside the object boundary. Unlike other analytic algorithms, the reconstruction time of SRT is comparable with that of FBP. The source code for SRT will become available in a future release of STIR.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Visual exploration of high-dimensional data through subspace analysis and dynamic projections

Here, we introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that create smooth animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evaluating the Effectiveness of a Detection and Deterrent System in Reducing Golden Eagle Fatalities at Operational Wind Facilities

The Renewable Energy Wildlife Institute (REWI) was appointed as the prime awardee of DOE award number DE-EE0007883 to lead a team of scientists, wind developers, and technology manufacturers toward the overarching goal of evaluating the effectiveness of the current DTBird system in minimizing the risk of golden eagles (Aquila chrysaetos) and other large soaring raptors from approaching the rotor-swept zone (RSZ) of operating wind turbines. As part of this goal, the team set out to 1) quantify the expected reduction in collision risk for golden eagles from operation of the detection and deterrence modules in a manner that supports the approach used by the U.S. Fish and Wildlife Service (USFWS) to assess and credit facility operators for their efforts to minimize predicted collision fatalities and 2) provide information to help improve the technology to maximize its effectiveness. DTBird is an automated detection and audio deterrent system created by the Spanish company Liquen, designed to discourage birds from entering the RSZ of spinning wind turbines. The system uses cameras to automatically detect airborne targets of interest, records each such event in an online database, and triggers a warning signal (loud sound) if the tracked object has moved close to the turbine. If the object moves even closer to the RSZ, a more aggressive dissuasion signal is broadcast. To meet our objectives, the team conducted a two-year experiment at the Goodnoe Hills wind facility in Washington state, in which 14 turbines were outfitted with DTBird units. Daily, each DTBird-equipped turbine was randomly assigned to a control or treatment group. Treatment turbines operated with DTBird running as intended—broadcasting warning or deterrent signals when DTBird detected a target within range. On control turbines, no sound signals were broadcast if a moving target triggered the DTBird system. The team also flew unmanned aerial vehicles (UAVs) designed to coarsely mimic the general size, weight, and coloration of golden eagles in programmed flight transects across DTBird detection ranges to quantify DTBird’s ability to detect intended targets and to evaluate factors that influence the probability of detection and DTBird’s response distances. Additionally, the team evaluated the behavioral responses of in situ eagles exposed to spinning turbines alone (visual and sound influences) versus spinning turbines plus broadcasted DTBird audio deterrents, to estimate the effectiveness of deterrence by the DTBird system. The data and results from these investigations were combined with those from a pilot study conducted at the Manzana Wind Power Project in California to better evaluate DTBird’s effectiveness across different landscapes.

17 WIND ENERGY↗
DOE OSTI2014

Web-based, GPU-accelerated, Monte Carlo simulation and visualization of indirect radiation imaging detector performance

Purpose: Monte Carlo simulations play a vital role in the understanding of the fundamental limitations, design, and optimization of existing and emerging medical imaging systems. Efforts in this area have resulted in the development of a wide variety of open-source software packages. One such package, hybridMANTIS, uses a novel hybrid concept to model indirect scintillator detectors by balancing the computational load using dual CPU and graphics processing unit (GPU) processors, obtaining computational efficiency with reasonable accuracy. In this work, the authors describe two open-source visualization interfaces, webMANTIS and visualMANTIS to facilitate the setup of computational experiments via hybridMANTIS. Methods: The visualization tools visualMANTIS and webMANTIS enable the user to control simulation properties through a user interface. In the case of webMANTIS, control via a web browser allows access through mobile devices such as smartphones or tablets. webMANTIS acts as a server back-end and communicates with an NVIDIA GPU computing cluster that can support multiuser environments where users can execute different experiments in parallel. Results: The output consists of point response and pulse-height spectrum, and optical transport statistics generated by hybridMANTIS. The users can download the output images and statistics through a zip file for future reference. In addition, webMANTIS provides a visualization window that displays a few selected optical photon path as they get transported through the detector columns and allows the user to trace the history of the optical photons. Conclusions: The visualization tools visualMANTIS and webMANTIS provide features such as on the fly generation of pulse-height spectra and response functions for microcolumnar x-ray imagers while allowing users to save simulation parameters and results from prior experiments. The graphical interfaces simplify the simulation setup and allow the user to go directly from specifying input parameters to receiving visual feedback for the model predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗