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Asteroids of various sizes, speeds, and compositions are zipping around the solar system with potential future Earth engagements. Most of the earth is covered in ocean and impacts would likely occur in deep ocean water. The IEEE SciVis Contest 2018 is dedicated to the visualization and analysis of simulations designed to study asteroid impacts in deep ocean water.
Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.
Nuflood Version 1.x is a surface-water hydrodynamic package designed for the simulation of overland flow of fluids. It consists of various routines to address a wide range of applications (e.g., rainfall-runoff, tsunami, storm surge) and real time, interactive visualization tools. Nuflood has been designed for general-purpose computers and workstations containing multi-core processors and/or graphics processing units. The software is easy to use and extensible, constructed in mind for instructors, students, and practicing engineers. Nuflood is intended to assist the water resource community in planning against water-related natural disasters.
We will present the use of immersive visualization at the National Renewable Energy Laboratory (NREL), showcasing how immersive visualization is advancing scientific research and engineering practices and transforming our day-to-day operations. We are leveraging immersive visualization to support scientific discovery and engineering in various domains, including material design, computational fluid dynamics, immersive analytics, grid modernization, digital twins, and situated visualization. We have observed several benefits across four key areas: enhanced spatial judgments, improved understanding through interaction, increased capacity to embed high-dimensional data, and improved collaboration.
Many research and development activities for scientific data analysis have focused on scalability challenges and data-driven features. Conversely, data visualization that focus on models requiring human interaction rarely involve practical and largescale scientific data analysis. Therefore, a gap exists between interactive data visualization and scientific data analysis applications. In this paper, we present a design study of interactive data visualization to support scientists who visually analyze data from neutron scattering experiments. This study was conducted in multiple phases: 1) problem characterization; 2) initial design and formative evaluation; and 3) iterative design. We characterize the problems and the design requirements for the analysis of the specific physical science data. We discuss the design, development, evaluation of our visual analytics tool and as well as our iterative developments with physical scientists. We show how to bridge the gap between the two disciplines uncovering new potential to solve their challenges in this design study. We focus on a specific challenge, finding an optimal color mapping, which plays a critical role in neutron scattering science and is broadly applicable to other scientific domains. To address the challenge, we propose two interactive visualization techniques: a dynamic color scale bar (DCSB) and a multi-scale histogram (MSH).
SCALE 6.2 consolidated the multiple special-purpose graphical user interfaces (GUI) of SCALE 6.1 into a completely new and modern interface called FULCRUM. FULCRUM is a cross-platform GUI designed to create, edit, validate, and visualize SCALE input, output, and data. It is intended to be usable by both novice and experienced SCALE users with an unobtrusive design. This paper presents a summary of FULCRUM capabilities. Specifically, interactive input validation, context-aware auto-completion, navigation, interactive geometry visualization with mesh results overlay, job execution, data plotting, and highly configurable workspace layouts will be discussed. (authors)
Combinatorial materials science experiments involve synthesis and spatially-resolved characterization of thin film sample libraries. As a result, the modern combinatorial materials science laboratory produces large, diverse, and complex data sets, requiring automation of analysis and visualization techniques. COMBIgor is a software package aimed to assist a combinatorial material scientists with large volumes of experimental data. This package, written in Igor Pro, offers a systematic approach to the loading, processing, and visualizing combinatorial data sets. COMBIgor is designed to be expanded on a laboratory, group, or individual basis to adopt additional loading, processing and visualization capabilities. By utilizing COMBIgor software package the burden of data management in combinatorial materials science experiments can be significantly reduced.
Soft errors have become one of the major concerns for the error resilience of the HPC applications as those errors may cause HPC applications to generate serious outcomes such as silent data corruptions (SDCs). Protecting the applications from soft errors is an essential while challenging task. Among different approaches, obtaining a profound understanding of the resilience proneness of an application is very important to devise efficient error detection and recovery strategies. Given the scale of the HPC applications both in the code size and execution time, there are often cases that the error propagation analysis on such applications would produce a massive volume of unstructured data, which requires a significant amount of efforts, to process and to obtain indicating actions towards error protection. In this paper, we present a control-flow based visual analysis framework to help the users conduct error propagation analysis and identify the critical sections of a program that may have a higher likelihood of leading to erroneous outcomes when affected by the control flow related errors. We also design and implement the scalable visualization framework - ResilienceVis that efficiently and effectively visualizes the affected program states under errors and the propagation traces for an application in a user-friendly manner, and eventually, we combine the analysis and visualization to exhibit the error-proneness of the different sections of applications.
Irrigation water delivery infrastructure, such as canals and pipelines, are essential to agriculture in the Western U.S., yet many of these systems are reaching the end of their useful lives. Reinvestment can achieve a wide variety of benefits, from water conservation to energy savings or renewable energy generation. Modernization requires significant planning, design, and implementation funding which can be a challenge for many irrigation districts. Here, this paper introduces IrrigationViz, a web-based mapping application designed to help irrigation districts visualize and generate high-level cost and benefit estimates for infrastructure modernization projects. These estimates can help water managers identify projects that benefit from additional engineering resources and ultimately obtain funding. IrrigationViz includes map interactions, graphs, and visualization components to facilitate planning and communication to stakeholders and funders. IrrigationViz combines user-provided information about a water-delivery system with public datasets and basic engineering formulas to generate estimates of the benefits of reinvestment. Estimates include the amount of water seepage in earthen canals, potential hydropower generation associated with replacing a canal with a pressurized pipe, and pipe size recommendations. We found that hydropower generation estimates compared favorably with real world projects, but seepage loss estimates showed high variability relative to on-the-ground measurements
SCALE 6.2 consolidated the multiple special-purpose graphical user interfaces (GUI) of SCALE 6.1 into a completely new and modern interface called Fulcrum. Fulcrum is a cross-platform GUI designed to create, edit, validate, and visualize SCALE input, output, and data. It is intended to be usable by both novice and experienced SCALE users with an unobtrusive design. This paper presents a summary of Fulcrum capabilities. Specifically, interactive input validation, context-aware auto-completion, navigation, interactive geome-try visualization with mesh results overlay, job execution, data plotting, and highly config-urable workspace layouts will be discussed.
X-ray imaging, which permits the microscopic visualization of metal alloy solidification dynamics, can be coupled with controlled solidification to create microstructures by design. This x-ray image shows a process-derived composite microstructure being made from a eutectic Al-17.1 at.%Cu alloy by successive solidification and remelting steps.
Radiation detection can provide a reliable means of detecting radiological material. Such capabilities can help to prevent nuclear and/or radiological attacks, but reliable detection in uncontrolled surroundings requires algorithms that account for environmental background radiation. The Berkeley Data Cloud (BDC) facilitates the development of such methods by providing a framework to capture, store, analyze, and share data sets. In the era of big data, both the size and variety of data make it difficult to explore and find data sets of interest and manage the data. Thus, in the context of big data, visualization is critical for checking data consistency and validity, identifying gaps in data coverage, searching for data relevant to an analyst's use cases, and choosing input parameters for analysis. Downloading the data and exploring it on an analyst's desktop using traditional tools are no longer feasible due to the size of the data. This study describes the design and implementation of a visualization system that addresses the problems associated with data exploration within the context of the BDC. Finally, the visualization system is based on a JavaScript front end communicating via REST with a back end web server.
Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.
In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.
Sandia National Laboratories is developing a new method for detecting penetration of tamper - indicating enclosures (TIEs). This method incorporates the use of "bleeding" materials (analogous to visually obvious, colorful bruised skin that doesn't heal) into the design of TIEs. As designed, it will allow inspectors to use simple visual observation to detect attempts to penetrate the external surfaces of a TIE, without providing adversaries the ability to repair damage. A material of this type can enhance tamper indication of current TIEs used to support treaty verification regimes. Current TIE inspections are time - consuming and rely on subjective visual assessment by an inspector, equipment such as eddy current or camera devices, or involve approaches that may be limited due to application environment. The complexities and requirements that volumetric sealing methods (or TIEs) must address are: (1) enclosures that are non - standard in size/shape; (2) enclosures that may be inspectorate - or facility - owned; (3) finding tamper attempts that are difficult and time consuming for an inspector to locate; (4) enclosures that are reliable and durable enough to survive the conditions that exist in the operating environment (including facility handling); and (5) methods that prevent adversaries from repairing penetrations. Early project R&D [1] focused on encapsulated transition metals. Due to the challenges associated with the transition metal - based approach, a mitigation approach was investigated resulting in two separate research paths — one that involves fabricating custom TIE molds that meet the specific (size and shape) needs of safeguards equipment a nd one that can be deployed as a sprayed on or painted coating to an existing TIE or surface. The "custom mold" approach is based on creating thin layers of materials that , when penetrated, expose an inner material to O 2 which causes an irreversible color change. The "in-situ coating" approach is based on applying a sensor solution containing color changing microcapsules that bleed when the microcapsule is ruptured. The anticipated benefits of this work are passive, flexible, scalable, robust , cost-effective TIEs with visually obvious responses to tamper attempts. This provides more efficient and effective monitoring , as inspectors will require little or no additional equipment and will be able to detect tamper without extensive time - consuming visual examination. Applications include custom TIEs (cabinets , equipment enclosures or seal bodies ), or spray-coating/painting onto facility-owned items, walls or structures, or circuit boards. The paper describes research and testing completed to-date on the method and integration of select system components.
Purpose: We propose a surface-image-guided soft robotic patient positioning system for maskless head-and-neck radiotherapy. The ultimate goal of this project is to utilize a soft robot to realize non-rigid patient positioning and real-time motion compensation. In this proof-of-concept study, we design a position-based visual servoing control system for an air-bladder-based soft robot and investigate its performance in controlling the flexion/extension cranial motion on a mannequin head phantom. Methods: The current system consists of Microsoft Kinect depth camera, an inflatable air bladder (IAB), pressured air source, pneumatic valve actuators, custom-built current regulators, and a National Instruments myRIO microcontroller. The performance of the designed system was evaluated on a mannequin head, with a ball joint fixed below its neck to simulate torso-induced head motion along flexion/extension direction. The IAB is placed beneath the mannequin head. The Kinect camera captures images of the mannequin head, extracts the face, and measures the position of the head relative to the camera. This distance is sent to the myRIO, which runs control algorithms and sends actuation commands to the valves, inflating and deflating the IAB to induce head motion. Results: For a step input, i.e. regulation of the head to a constant displacement, the maximum error was a 6% overshoot, which the system then reduces to 0% steady-state error. In this initial investigation, the settling time to reach the regulated position was approximately 8 seconds, with 2 seconds of delay between the command start of motion due to capacitance of the pneumatics, for a total of 10 seconds to regulate the error. Conclusion: The surface image-guided soft robotic patient positioning system can achieve accurate mannequin head flexion/extension motion. Given this promising initial Result, the extension of the current one-dimensional soft robot control to multiple IABs for non-rigid positioning control will be pursued.
A controlled between-groups experiment was conducted to demonstrate the value of human factors for process design. Most evidence to convey the benefits of human factors is derived from reactive studies of existing flawed systems designed with little or no human factors involvement. Controlled experiments conducted explicitly to demonstrate the benefits of human factors have been scarce since the 1990s. Further, most previous research focused on product or interface design as opposed to process design. The present study was designed to fill these research gaps. Toward that end, 24 Sandia National Laboratories employees completed a simple visual inspection task simulating receipt inspection. The experimental group process was designed to conform to human factors and visual inspection principles, whereas the control group process was designed without consideration of such principles. Results indicated the experimental group exhibited superior performance accuracy, lower workload, and more favorable usability ratings as compared to the control group. Given the differences observed in the simple task used in the present study, the author concluded that incorporating human factors should have even greater benefits for complex products and processes. The study provides evidence to help human factors practitioners revitalize the critical message regarding the benefits of human factors involvement for a new generation of designers.
The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater Remediation, is supporting multi-laboratory development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is an open source and modular computing framework that incorporates new advances and tools for predicting contaminant fate and transport in natural and engineered systems. ASCEM facilitates transparent, efficient and integrated approaches to modeling and site characterization, and provides robust and standardized assessments of performance and risk for EM cleanup and closure activities. Site subsurface simulation modeling and performance assessments are complex and involve sensitivity evaluations and uncertainty quantification to better understand the risks at a site. The ASCEM tool-set was designed in close collaboration with the sites and other potential end-users (both the public and regulators) to allow better communication and understanding of these complex modeling efforts. ASCEM's integrated tool-sets provide a user interface and tools for managing work-flows, including conceptual model development, management of data and metadata for model input, sensitivity analysis, model calibration and uncertainty analysis, model execution on diverse computational platforms, and processing of model output, including visualization. The hierarchical and modular design of ASCEM HPC simulator Amanzi easily lends itself to translating this conceptual model of a site into a numerical model that can easily be spatially and temporally discretized to run on the HPC simulator. Together this integrated work-flow allows for a seamless and integrated analysis tracking all provenance information and modeling uncertainties. (authors)