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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Dry Eye Syndrome After Proton Therapy of Ocular Melanomas

Purpose: To investigate whether proton therapy (PT) performs safely in superotemporal melanomas, in terms of risk of dry-eye syndrome (DES). Methods and Materials: Tumor location, DES grade, and dose to ocular structures were analyzed in patients undergoing PT (2005-2015) with 52 Gy (prescribed dose, not accounting for biologic effectiveness correction of 1.1). Prognostic factors of DES and severe DES (sDES, grades 2-3) were determined with Cox proportional hazard models. Visual acuity deterioration and enucleation rates were compared by sDES and tumor locations. Results: Median follow-up was 44 months (interquartile range, 18-60 months). Of 853 patients (mean age, 64 years), 30.5% had temporal and 11.4% superotemporal tumors. Five-year incidence of DES and sDES was 23.0% (95% confidence interval [CI] 19.0%-27.7%) and 10.9% (95% CI 8.2%-14.4%), respectively. Multivariable analysis showed a higher risk for sDES in superotemporal (hazard ratio [HR] 5.82, 95% CI 2.72-12.45) and temporal tumors (HR 2.63, 95% CI 1.28-5.42), age ≥70 years (HR 1.90, 95% CI 1.09-3.32), distance to optic disk ≥5 mm (HR 2.71, 95% CI 1.52-4.84), ≥35% of retina receiving 12 Gy (HR 2.98, 95% CI 1.54-5.77), and eyelid rim irradiation (HR 2.68, 95% CI 1.49-4.80). The same risk factors were found for DES. Visual acuity deteriorated more in patients with sDES (0.86 ± 1.10 vs 0.64 ± 0.98 logMAR, P=.034) but not between superotemporal/temporal and other locations (P=.890). Enucleation rates were independent of sDES (P=.707) and tumor locations (P=.729). Conclusions: Severe DES was more frequent in superotemporal/temporal melanomas. Incidence of vision deterioration and enucleation was no higher in patients with superotemporal melanoma than in patients with tumors in other locations. Tumor location should not contraindicate PT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

A Visual Designer of Layer‐wise Relevance Propagation Models

Abstract Layer‐wise Relevance Propagation (LRP) is an emerging and widely‐used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a “best” LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance‐based visual analysis with two important functions: relevance‐based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.

Huang, Xinyi↗
DOE OSTI2023

Electrophysiological Signatures of Visual Recognition Memory across All Layers of Mouse V1

In mouse primary visual cortex (V1), familiar stimuli evoke significantly altered responses when compared with novel stimuli. This stimulus-selective response plasticity (SRP) was described originally as an increase in the magnitude of visual evoked potentials (VEPs) elicited in layer 4 (L4) by familiar phase-reversing grating stimuli. SRP is dependent on NMDA receptors (NMDARs) and has been hypothesized to reflect potentiation of thalamocortical (TC) synapses in L4. However, recent evidence indicates that the synaptic modifications that manifest as SRP do not occur on L4 principal cells. To shed light on where and how SRP is induced and expressed in male and female mice, the present study had three related aims: (1) to confirm that NMDAR are required specifically in glutamatergic principal neurons of V1, (2) to investigate the consequences of deleting NMDAR specifically in L6, and (3) to use translaminar electrophysiological recordings to characterize SRP expression in different layers of V1. We find that knock-out (KO) of NMDAR in L6 principal neurons disrupts SRP. Current-source density (CSD) analysis of the VEP depth profile shows augmentation of short latency current sinks in layers 3, 4, and 6 in response to phase reversals of familiar stimuli. Multiunit recordings demonstrate that increased peak firing occurs in response to phase reversals of familiar stimuli across all layers, but that activity between phase reversals is suppressed. Together, these data reveal important aspects of the underlying phenomenology of SRP and generate new hypotheses for the expression of experience-dependent plasticity in V1. SIGNIFICANCE STATEMENT Repeated exposure to stimuli that portend neither reward nor punishment leads to behavioral habituation, enabling organisms to dedicate attention to novel or otherwise significant features of the environment. The neural basis of this process, which is so often dysregulated in neurologic and psychiatric disorders, remains poorly understood. Learning and memory of stimulus familiarity can be studied in mouse visual cortex by measuring electrophysiological responses to simple phase-reversing grating stimuli. The current study advances knowledge of this process by documenting changes in visual evoked potentials (VEPs), neuronal spiking activity, and oscillations in the local field potentials (LFPs) across all layers of mouse visual cortex. In addition, we identify a key contribution of a specific population of neurons in layer 6 (L6) of visual cortex.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-09: Image Quality Comparison and Dose Quantification for 2.5 MV

Purpose: To compare the image quality of the 2.5MV imaging beam (2.5X-IMB) to that of a 6MV beam and to quantify the imaging dose of a 2.5X-IMB for constancy as specified by AAPM TG-142 Methods: The image quality of the 2.5X-IMB was compared to the 6MV imaging beam using the SNC ImagePro MV-QA phantom and the Varian supplied Las Vegas phantom (LVP). High resolution (1280×1280×16, 2 frames at 1.5MU/frame) and low resolution (640×640×16, 2 frames at 0.75MU/frame) images were compared for each phantom. MV-QA phantom images were evaluated quantitatively, and the LVP images were evaluated qualitatively. The imaging dose for 2.5X-IMB was quantified using the procedure outlined in TG51. PTWCC13-31013 chambers were used to measure a percent depth dose (PDD) curve for the 2.5X-IMB. All the factors described in TG51 were calculated using the 2.5X-IMB and a PTW30013 farmer chamber. Results: A comparison between 2.5X-IMB and 6MV image quality was performed both visually and with DoseLab software. The optimal window and level were set for each image of the LVP by the user. Visual inspection showed greater contrast resolution with the 2.5MV beam, but no significant difference with the change in imaging resolution. DoseLab reported similar spatial resolutions between the two energies, but the contrast-to-noise ratio (CNR) was greater for 2.5MV. The PDDx(10cm) for a 10x10cm2 field was measured to be 51.5%. Although this PDD value is off the scale of Figure 4 in TG51, the trend of the curve corresponding to the PTW31003 (equivalent) chamber led to an approximate kQ value of 1.00. Conclusion: When compared to 6MV imaging, 2.5X-IMB results in a better CNR. At low resolution, the DoseLab results for the two energies are comparable, but visual analysis favors the 2.5X-IMB images. Imaging dose was quantified for the 2.5X-IMB after following the TG51 methodology with appropriate approximations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Performance Monitoring Program: Developing Comparative Metrics for Fitness-for-Duty Programs

To comply with U.S. Nuclear Regulatory Commission (NRC) regulations, licensees and entities authorized under Title 10 of the Code of Federal Regulations (CFR) Part 26 Section 26.3 (§ 26.3) are required to have fitness-for-duty (FFD) programs. Under § 26.3, the expectation of these FFD programs is to provide reasonable assurance that individuals who are granted unescorted access to nuclear power reactor protected areas and Category I fuel cycle facility material control areas are trustworthy, will perform their tasks in a reliable manner, are not under the influence of any substance, legal or illegal, that may impair their ability to perform their duties, and are not mentally or physically impaired from any cause that can adversely affect their ability to safely and competently perform their duties. Pacific Northwest National Laboratory (PNNL) was tasked with developing a performance monitoring program to risk inform NRC inspection and policy regarding quantitative FFD performance data. To meet this need, PNNL developed methodologies that could be implemented within a performance monitoring program. Throughout this report, these methodologies are referred to as comparative metrics. The NRC provided PNNL with 2016–2019 data from annual reporting forms and single positive test forms provided by licensees and other entities. For most of the comparative metrics, the analyses required customized processing, such as creating filtering fields, adding data fields and summaries, and joining datasets. The comparative metrics developed include: random testing rate, random policy violation rate, pre-access policy violation rate, subversion attempt rate, and number of policy violations by labor category. The comparative metrics can be used for parsing and visualizing FFD program data and monitoring FFD performance at the labor category, facility, licensee, and industry levels to risk inform NRC inspection and policy with regard to the FFD data currently collected from licensees and other entities that implement Part 26 requirements. Furthermore, these developed comparative metrics allow a more in-depth look at the FFD programs for the industry to discern trends and patterns that may warrant changes at an industry level and to inform policy decisions. These analyses should be refreshed as new FFD data become available.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Diverging polygon-based modeling (DPBM) of concentrated solar flux distributions

This paper presents an efficient and robust methodology for modeling concentrated solar flux distributions. Compared to ray tracing methods, which provide high accuracy but can be computationally intensive, this approach makes a number of simplifying assumptions in order to reduce complexity by modeling incident and reflected flux as a series of simple geometric diverging polygons, then applying shading and blocking effects. A reduction in processing time (as compared to ray tracing) allows for evaluating and visualizing numerous combinations of engineering and operational variables (easily exceeding 106 unique iterations) to ascertain instantaneous, transient, and annual system performance. The method is demonstrated on a linear Fresnel reflector array and a number of variable iteration examples presented. While some precision is sacrificed for computational speed, flux distributions were compared to ray tracing (SolTrace) and average concentration ratio generally found to agree within ~3%. Furthermore, this method presents a quick and very flexible coarse adjust method for concentrated solar power (CSP) field design, and can be used to both rapidly gain an understanding of system performance as well as to narrow variable constraint windows for follow-on high accuracy system optimization.

14 SOLAR ENERGY↗
DOE OSTI2023

Twisted Crystalline Organic Semiconductor Photodetectors

Optoelectronic properties of anisotropic crystals vary with direction requiring that the orientation of molecular organic semiconductor crystals is controlled in optoelectronic device active layers to achieve optimal performance. Here, in this work, a generalizable strategy to introduce periodic variations in the out-of-plane orientations of 5,11-bis(triisopropylsilylethynyl)anthradithiophene (TIPS ADT) crystals is presented. TIPS ADT crystallized from the melt in the presence of 16 wt.% polyethylene (PE) forms banded spherulites of crystalline fibrils that twist in concert about the radial growth direction. These spherulites exhibit band-dependent light absorption, photoluminescence, and Raman scattering depending on the local orientation of crystals. Mueller matrix imaging reveals strong circular extinction (CE), with TIPS ADT banded spherulites exhibiting domains of positive or negative CE signal depending on the crystal twisting sense. Furthermore, orientation-dependent enhancement in charge injection and extraction in films of twisted TIPS ADT crystals compared to films of straight crystals is visualized in local conductive atomic force microscopy maps. This enhancement leads to 3.3- and 6.2-times larger photocurrents and external quantum efficiencies, respectively, in photodetectors comprising twisted crystals than those comprising straight crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A facile route towards large area self-assembled nanoscale silver film morphologies and their applications towards metal enhanced fluorescence

Here, we present a facile method for fabricating nanostructured silver films containing a high density of nanoscopic gap features through a surface directed phenomenon utilizing nanoporous scaffolds rather than through traditional lithographic patterning processes. This method enables tunability of the silver film growth by simply adjusting the formulation and processing conditions of the nanoporous film prior to metallization. We further demonstrate that this process can produce nanoscopic gaps in thick (100 nm) silver films supporting localized surface plasmon resonance with large field amplification within the gaps while enabling launching of propagating surface plasmons within the silver grains. These enhanced fields provide metal enhanced fluorescence with enhancement factors as high as 21 times compared to glass, as well as enable visualization of single fluorophore emission. This work provides a low-cost rapid approach for producing novel nanostructures capable of broadband fluorescence amplification, with potential applications including plasmonic and fluorescence based optical sensing and imaging applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Microchannel Geometries for Improved Heat Transfer with Low-GWP refrigerants

Due to efforts aimed at decarbonizing industries, the use of refrigerants with low global warming potential (GWP) is highly recommended in the air-conditioning and refrigeration sectors. Despite possessing low-GWP values of less than 150, hydrofluoroolefins (HFO) exhibit relatively lower heat transfer performance compared to conventional hydrofluorocarbons (HFC) under certain operating conditions. In contrast to HFCs, there is a high demand for enhanced surfaces to meet the needs of heat transfer systems utilizing low GWP refrigerants. Accordingly, this study analyzes the pool boiling performance of low-GWP refrigerants in microchannel geometries. The experiments were carried out at various heat flux levels on both smooth and enhanced surfaces. The pool boiling behavior of low-GWP refrigerant R1234yf was compared to that of R-134a refrigerant in terms of heat transfer coefficient and wall superheat. The results indicate that the heat transfer coefficients of the enhanced surface are significantly higher than those of the smooth surface. Furthermore, the microchannel geometry demonstrated a lower wall superheat compared to the smooth surface. Additionally, a visualization study was performed using a high-speed camera to understand the pool boiling mechanism of low-GWP refrigerants on both smooth and enhanced surfaces.

Murugan, Muneeshwaran↗
DOE OSTI2022

Circular Trajectory Approach for Online Sinusoidal Signal Distortion Monitoring and Visualization

The increasing complexity and uncertainties of modern power systems are placing significant demands on signal monitoring techniques. This work proposes the Circular Trajectory Approach (CTA) for online sinusoidal signal distortion monitoring and visualization. CTA can detect distortions of a sinusoidal signal. Compared with existing waveform anomaly detection techniques, CTA is faster in detection and less computation intensive. It thus supports edge devices and online applications. CTA also offers a new means of sinusoidal signal distortion visualization. It can reveal the distorted sections in a sinusoidal cycle and clearly display the distortions. The proposed approach is tested on real data from an open source EPRI dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Preserving Contextual Awareness during Selection of Moving Targets in Animated Stream Visualizations

In many types of dynamic interactive visualizations, it is often desired to interact with moving objects. Stopping moving objects can make selection easier, but pausing animated content can disrupt perception and understanding of the visualization. To address such problems, we explore selection techniques that only pause a subset of all moving targets in the visualization. We present various designs for controlling pause regions based on cursor trajectory or cursor position. We then report a dual-task experiment that evaluates how different techniques affect both target selection performance and contextual awareness of the visualization. Our findings indicate that all pause techniques significantly improved selection performance as compared to the baseline method without pause, but the results also show that pausing the entire visualization can interfere with contextual awareness. However, the problem with reduced contextual awareness was not observed with our new techniques that only pause a limited region of the visualization. Thus, our research provides evidence that region-limited pause techniques can retain the advantages of selection in dynamic visualizations without imposing a negative effect on contextual awareness.

Ragan, Eric↗
DOE OSTI2019

Classification of Broad Absorption Line Quasars with a Convolutional Neural Network

Quasars that exhibit blueshifted, broad absorption lines (BAL QSOs) are an important probe of black hole feedback on galaxy evolution. Yet the presence of BALs is also a complication for large spectroscopic surveys that use quasars as cosmological probes because the BAL features can affect redshift measurements and contaminate information about the matter distribution in the Lyα forest. We present a new BAL QSO catalog for quasars in the Sloan Digital Sky Survey (SDSS) Data Release 14 (DR14). As the SDSS DR14 quasar catalog has over 500,000 quasars, we have developed an automated BAL classifier with a Convolutional Neural Network (CNN). We trained our CNN classifier on the C IV λ 1549 region of a sample of quasars with reliable human classifications, and compared the results to both a dedicated test sample and visual classifications from the earlier SDSS DR12 quasar catalog. Our CNN classifier correctly classifies over 98% of the BAL quasars in the DR12 catalog, which demonstrates comparable reliability to human classification. The disagreements are generally for quasars with lower signal-to-noise ratio spectra and/or weaker BAL features. Our new catalog includes the probability that each quasar is a BAL, the strength, blueshifts and velocity widths of the troughs, and similar information for any Si IV λ 1398 BAL troughs that may be present. We find significant BAL features in 16.8% of all quasars with 1.57 < z < 5.56 in the SDSS DR14 quasar catalog.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Framework for Analysis and Visualization of Simulation Data (VizAly)

As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the cosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational data sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing platforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.

Wendelberger, Joanne↗
DOE OSTI2014

Acoustic Monitoring of Beluga Whale Interactions with Cook Inlet Tidal Energy Project

Cook Inlet, Alaska is home to some of the greatest tidal energy resources in the U.S., as well as an endangered population of beluga whales (Delphinapterus leucas). Successfully permitting and operating a tidal power project in Cook Inlet requires a biological assessment of the potential and realized effects of the physical presence and sound footprint of tidal turbines on the distribution, relative abundance, and behavior of Cook Inlet beluga whales. ORPC Alaska, working with the Project Team—LGL Alaska Research Associates, University of Alaska Anchorage, TerraSond, and Greeneridge Science—undertook the following U.S. Department of Energy (DOE) study to characterize beluga whales in Cook Inlet – Acoustic Monitoring of Beluga Whale Interactions with the Cook Inlet Tidal Energy Project (Project). ORPC Alaska, LLC, is a wholly-owned subsidiary of Ocean Renewable Power Company, LLC, (collectively, ORPC). ORPC is a global leader in the development of hydrokinetic power systems and eco-conscious projects that harness the power of ocean and river currents to create clean, predictable renewable energy. ORPC is developing a tidal energy demonstration project in Cook Inlet at East Foreland where ORPC has a Federal Energy Regulatory Commission (FERC) preliminary permit (P-13821). The Project collected baseline data to characterize pre-deployment patterns of marine mammal distribution, relative abundance, and behavior in ORPC’s proposed deployment area at East Foreland. ORPC also completed work near Fire Island where ORPC held a FERC preliminary permit (P-12679) until March 6, 2013. Passive hydroacoustic devices (previously utilized with bowhead whales in the Beaufort Sea) were adapted for study of beluga whales to determine the relative abundance of beluga whale vocalizations within the proposed deployment areas. Hydroacoustic data collected during the Project were used to characterize the ambient acoustic environment of the project site pre-deployment to inform the FERC pilot project process. The Project compared results obtained from this method to results obtained from other passive hydrophone technologies and to visual observation techniques performed simultaneously. This Final Report makes recommendations on the best practice for future data collection, for ORPC’s work in Cook Inlet specifically, and for tidal power projects in general. This Project developed a marine mammal study design and compared technologies for hydroacoustic and visual data collection with potential for broad application to future tidal and hydrokinetic projects in other geographic areas. The data collected for this Project will support the environmental assessment of future Cook Inlet tidal energy projects, including ORPC’s East Foreland Tidal Energy Project and any tidal energy developments at Fire Island. The Project’s rigorous assessment of technology and methodologies will be invaluable to the hydrokinetic industry for developing projects in an environmentally sound and sustainable way for areas with high marine mammal activity or endangered populations. By combining several different sampling methods this Project will also contribute to the future preparation of a comprehensive biological assessment of ORPC’s projects in Cook Inlet.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Leveraging Prior Concept Learning Improves Generalization From Few Examples in Computational Models of Human Object Recognition

Humans quickly and accurately learn new visual concepts from sparse data, sometimes just a single example. The impressive performance of artificial neural networks which hierarchically pool afferents across scales and positions suggests that the hierarchical organization of the human visual system is critical to its accuracy. These approaches, however, require magnitudes of order more examples than human learners. We used a benchmark deep learning model to show that the hierarchy can also be leveraged to vastly improve the speed of learning. We specifically show how previously learned but broadly tuned conceptual representations can be used to learn visual concepts from as few as two positive examples; reusing visual representations from earlier in the visual hierarchy, as in prior approaches, requires significantly more examples to perform comparably. These results suggest techniques for learning even more efficiently and provide a biologically plausible way to learn new visual concepts from few examples.

Rule, Joshua S.↗
DOE OSTI2024

A multiscale anisotropic polymer network model coupled with phase field fracture

The study of polymers has continued to gain substantial attention due to their expanding range of applications, spanning essential engineering fields to emerging domains like stretchable electronics, soft robotics, and implantable sensors. These materials exhibit remarkable properties, primarily stemming from their intricate polymer chain network, which, in turn, increases the complexity of precisely modeling their behavior. Especially for modeling elastomers and their fracture behavior, accurately accounting for the deformations of the polymer chains is vital for predicting the rupture in highly stretched chains. Despite the importance, many robust multiscale continuum frameworks for modeling elastomer fracture tend to simplify network deformations by assuming uniform behavior among chains in all directions. Recognizing this limitation, our study proposes a multiscale fracture model that accounts for the anisotropic nature of elastomer network responses. At the microscale, damage in the chains is assumed to be driven by both the chain's entropy and the internal energy due to molecular bond distortions. In order to bridge the stretching in the chains to the macroscale deformation, we employ the maximal advance path constraint network model, inherently accommodating anisotropic network responses. As a result, chains oriented differently can be predicted to exhibit varying stretch and, consequently, different damage levels. To drive macroscale fracture based on damages in these chains, we utilize the micromorphic regularization theory, which involves the introduction of dual local-global damage variables at the macroscale. The macroscale local damage variable is obtained through the homogenization of the chain damage values, resulting in the prediction of an isotropic material response. The macroscale global damage variable is subjected to nonlocal effects and boundary conditions in a thermodynamically consistent phase field continuum formulation. Moreover, the total dissipation in the system is considered to be mainly due to the breaking of the molecular bonds at the microscale. To validate our model, we employ the double-edge notched tensile test as a benchmark, comparing simulation predictions with existing experimental data. Additionally, to enhance our understanding of the fracturing process, we conduct uniaxial tensile experiments on a square film made up of polydimethylsiloxane (PDMS) rubber embedded with a hole and notches and then compare our simulation predictions with the experimental observations. Furthermore, we visualize the evolution of stretch and damage values in chains oriented along different directions to assess the predictive capacity of the model. In conclusion, the results are also compared with another existing model to evaluate the utility of our model in accurately simulating the fracture behavior of rubber-like materials.

42 ENGINEERING↗
DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗
DOE OSTI2021

A Visual Designer of Layer-wise Relevance Propagation Models

Layer-wise Relevance Propagation (LRP) is an emerging and widely-used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a "best" LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance-based visual analysis with two important functions: relevance-based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.

97 MATHEMATICS AND COMPUTING↗