Design of a simulated cruise scene visual attachment. Volume 1 - Design report
Television-type, out-window visual simulation image generator design and specifications for aircraft or spacecraft manned flight simulation
Kielar, C. W.↗
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Results for “Design Visualization”
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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Of red planets and indigo computers: Mars database visualization as an example of platform downsizing
The last decade has witnessed tremendous advancements in the computer hardware and software used to perform scientific visualization. In this paper, we consider how the visualization of a particular data set, the digital terrain model derived from the Viking orbiter imagery, has been realized in four distinct projects over this period. These examples serve to demonstrate how the vast improvements in computational performance both decrease the cost of such visualization efforts and permit an increasing level of interactivity. We then consider how even today's graphical systems require the visualization designer to make intelligent choices and tradeoffs in database rendering. Finally, we discuss how insights gleaned from an understanding of human visual perception can guide these design decisions, and suggest new options for visualization hardware and software.
NASA Center ARC↗
Downsizing Visualization Platforms: From Crays to Indigos and Beyond
Despite its increasingly negative connotation in other domains, "downsizing" is a positive trend as it applies to the computer hardware necessary to perform scientific visualization. In this talk, we will consider how the visualization of a particular data set, the Digital Terrain Model (DTM) derived from the Viking Orbiter imagery, has been realized in three distinct projects over the past decade. These examples serve to demonstrate how the vast improvements in computational performance both decrease the cost of such visualization efforts, and permit an increasing level of interactivity. We then consider how even today's graphical systems require the visualization designer to make intelligent choices and trade-offs in database rendering. Finally, we discuss how insights from an understanding of human visual perception can guide these design decisions, and suggest new options for visualization hardware and software.
Kaiser, Mary K.↗
Visualization for Insight and Data Analysis in Energy Research
This talk explores how advanced visualization technologies are transforming analytical reasoning and knowledge discovery in energy research, drawing on recent work at the National Laboratory of the Rockies' Computational Science Center. Through a series of scientific case studies, we demonstrate how immersive and high-resolution visualization environments enable scientists and engineers to identify previously unseen patterns and features - insights that often remain hidden in traditional desktop-based analysis. By embedding richer information into interactive analytics tools, these approaches support the exploration of complex, multivariate parameter spaces, where interaction itself catalyzes understanding. Beyond capability, we emphasize the critical role of visualization design grounded in perception and cognition, showing how visual encodings directly influence analytical outcomes. Spanning applications from materials science to integrated energy systems, these visualization approaches accelerate innovation and improve decision-making by enabling deeper, more reliable insight into increasingly complex energy data.
97 MATHEMATICS AND COMPUTING↗
DCT quantization matrices visually optimized for individual images
This presentation describes how a vision model incorporating contrast sensitivity, contrast masking, and light adaptation is used to design visually optimal quantization matrices for Discrete Cosine Transform image compression. The Discrete Cosine Transform (DCT) underlies several image compression standards (JPEG, MPEG, H.261). The DCT is applied to 8x8 pixel blocks, and the resulting coefficients are quantized by division and rounding. The 8x8 'quantization matrix' of divisors determines the visual quality of the reconstructed image; the design of this matrix is left to the user. Since each DCT coefficient corresponds to a particular spatial frequency in a particular image region, each quantization error consists of a local increment or decrement in a particular frequency. After adjustments for contrast sensitivity, local light adaptation, and local contrast masking, this coefficient error can be converted to a just-noticeable-difference (jnd). The jnd's for different frequencies and image blocks can be pooled to yield a global perceptual error metric. With this metric, we can compute for each image the quantization matrix that minimizes the bit-rate for a given perceptual error, or perceptual error for a given bit-rate. Implementation of this system demonstrates its advantages over existing techniques. A unique feature of this scheme is that the quantization matrix is optimized for each individual image. This is compatible with the JPEG standard, which requires transmission of the quantization matrix.
Watson, Andrew B.↗
A Case Study: Using Delmia at Kennedy Space Center to Support NASA's Constellation Program
The presentation examines the use of Delmia (Digital Enterprise Lean Manufacturing Interactive Application) for digital simulation in NASA's Constellation Program. Topics include an overview of the Kennedy Space Center (KSC) Design Visualization Group tasks, NASA's Constellation Program, Ares 1 ground processing preliminary design review, and challenges and how Delmia is used at KSC, Challenges include dealing with large data sets, creating and maintaining KSC's infrastructure, gathering customer requirements and meeting objectives, creating life-like simulations, and providing quick turn-around on varied products,
Kickbusch, Tracey↗
Scalable Comparative Visualization of Ensembles of Call Graphs
Optimizing the performance of large-scale parallel codes is critical for efficient utilization of computing resources. Code developers often explore various execution parameters, such as hardware configurations, system software choices, and application parameters, and are interested in detecting and understanding bottlenecks in different executions. They often collect hierarchical performance profiles represented as call graphs, which combine performance metrics with their execution contexts. The crucial task of exploring multiple call graphs together is tedious and challenging because of the many structural differences in the execution contexts and significant variability in the collected performance metrics (e.g., execution runtime). In this paper, we present Ensemble CallFlow to support the exploration of ensembles of call graphs using new types of visualizations, analysis, graph operations, and features. We introduce ensemble-Sankey , a new visual design that combines the strengths of resource-flow (Sankey) and box-plot visualization techniques. Whereas the resource-flow visualization can easily and intuitively describe the graphical nature of the call graph, the box plots overlaid on the nodes of Sankey convey the performance variability within the ensemble. Our interactive visual interface provides linked views to help explore ensembles of call graphs, e.g., by facilitating the analysis of structural differences, and identifying similar or distinct call graphs. Finally, we demonstrate the effectiveness and usefulness of our design through case studies on large-scale parallel codes.
97 MATHEMATICS AND COMPUTING↗
CATIA V5 Virtual Environment Support for Constellation Ground Operations
This summer internship primarily involved using CATIA V5 modeling software to design and model parts to support ground operations for the Constellation program. I learned several new CATIA features, including the Imagine and Shape workbench and the Tubing Design workbench, and presented brief workbench lessons to my co-workers. Most modeling tasks involved visualizing design options for Launch Pad 39B operations, including Mobile Launcher Platform (MLP) access and internal access to the Ares I rocket. Other ground support equipment, including a hydrazine servicing cart, a mobile fuel vapor scrubber, a hypergolic propellant tank cart, and a SCAPE (Self Contained Atmospheric Protective Ensemble) suit, was created to aid in the visualization of pad operations.
Kelley, Andrew↗
Trust Your Gut: Comparing Human and Machine Inference from Noisy Visualizations
People commonly utilize visualizations not only to examine a given dataset, but also to draw generalizable conclusions about the underlying models or phenomena. Prior research has compared human visual inference to that of an optimal Bayesian agent, with deviations from rational analysis viewed as problematic. However, human reliance on non-normative heuristics may prove advantageous in certain circumstances. We investigate scenarios where human intuition might surpass idealized statistical rationality. In two experiments, we examine individuals’ accuracy in characterizing the parameters of known data-generating models from bivariate visualizations. Our findings indicate that, although participants generally exhibited lower accuracy compared to statistical models, they frequently outperformed Bayesian agents, particularly when faced with extreme samples. Participants appeared to rely on their internal models to filter out noisy visualizations, thus improving their resilience against spurious data. However, participants displayed overconfidence and struggled with uncertainty estimation. They also exhibited higher variance than statistical machines. Our findings suggest that analyst gut reactions to visualizations may provide an advantage, even when departing from rationality. These results carry implications for designing visual analytics tools, offering new perspectives on how to integrate statistical models and analyst intuition for improved inference and decision-making. The data and materials for this paper are available at https://osf.io/qmfv6
human-machine collaboration↗
Modeling and evaluating user behavior in exploratory visual analysis
Empirical evaluation methods for visualizations have traditionally focused on assessing the outcome of the visual analytic process as opposed to characterizing how that process unfolds. There are only a handful of methods that can be used to systematically study how people use visualizations, making it difficult for researchers to capture and characterize the subtlety of cognitive and interaction behaviors users exhibit during visual analysis. To validate and improve visualization design, however, it is important for researchers to be able to assess and understand how users interact with visualization systems under realistic scenarios. This paper presents a methodology for modeling and evaluating the behavior of users in exploratory visual analysis. We model visual exploration using a Markov chain process comprising transitions between mental, interaction, and computational states. These states and the transitions between them can be deduced from a variety of sources, including verbal transcripts, videos and audio recordings, and log files. This model enables the evaluator to characterize the cognitive and computational processes that are essential to insight acquisition in exploratory visual analysis, and reconstruct the dynamics of interaction between the user and the visualization system. We illustrate this model with two exemplar user studies, and demonstrate the qualitative and quantitative analytical tools it affords.
97 MATHEMATICS AND COMPUTING↗
Report for the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication
Visualization—the use of visual elements to explore data, form hypotheses, or convey conclusions—is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes for the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality (VR) and artificial intelligence (AI), visualization has become increasingly essential but also ever more challenging. The Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing as well as for DOE-relevant applications and goals in general. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision making, and communication. The first three PRDs describe interconnected research themes addressing the need for new techniques to deal with complex data, uncertainty, and interpretability (PRD 1); the need for scalable and interoperable software stacks (PRD 2); and the challenges and opportunities inherent in new technologies, such as VR, cloud, or exascale computing (PRD 3). The remaining two PRDs describe foundational research themes that recognize the potential of visualizations to provide equitable access to information and to strengthen the scientific discourse (PRD 4); and the need to consider human factors when designing visualizations (PRD 5). Collectively, these PRDs form the pillars for a coherent, long-term research and development strategy in Visualization for Scientific Discovery, Decision-Making, and Communication in the context of the Office of Science’s mission scope.
97 MATHEMATICS AND COMPUTING↗
A Prospective Design Method for Nuclear Power: The Evaluation, Requirements, and Goals Outline for Nuclear (ERGON) Method
Human factors researchers at Idaho National Laboratory (INL) have worked on projects spanning control room modernization, operator support systems, visualization design, and novel system creation. These projects demonstrated the need for an explicit design method for nuclear power. Human factors teams found a high standard in the Human Factors Engineering Program Review Model (NUREG-0711) and needed a design methodology which could be successful in gaining approval. Previous work has been synthesized as the Evaluation, Requirements, and Goals Outline for Nuclear (ERGON) method here. Design tasks are broken into four phases: Context and Orientation, Human Factors Review, Prototyping and Evaluation, Iteration and Improvement. ERGON is intended as a flexible and direct design method for many applications in nuclear power. ERGON has been vetted through collaborative research and development with nuclear utilities and as such, the ERGON method can assist utilities to achieve approval from a NUREG-0711 summative evaluation for HSI implementations.
42 ENGINEERING↗
Applications of Modeling and Simulation for Flight Hardware Processing at Kennedy Space Center
The Boeing Design Visualization Group (DVG) is responsible for the creation of highly-detailed representations of both on-site facilities and flight hardware using computer-aided design (CAD) software, with a focus on the ground support equipment (GSE) used to process and prepare the hardware for space. Throughout my ten weeks at this center, I have had the opportunity to work on several projects: the modification of the Multi-Payload Processing Facility (MPPF) High Bay, weekly mapping of the Space Station Processing Facility (SSPF) floor layout, kinematics applications for the Orion Command Module (CM) hatches, and the design modification of the Ares I Upper Stage hatch for maintenance purposes. The main goal of each of these projects was to generate an authentic simulation or representation using DELMIA V5 software. This allowed for evaluation of facility layouts, support equipment placement, and greater process understanding once it was used to demonstrate future processes to customers and other partners. As such, I have had the opportunity to contribute to a skilled team working on diverse projects with a central goal of providing essential planning resources for future center operations.
Marshall, Jennifer L.↗
Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net-Load Forecasting
Accurate net-load forecasting is vital for energy planning, aiding decisions on trade and load distribution. However, assessing the performance of forecasting models across diverse input variables, like temperature and humidity, remains challenging, particularly for eliciting a high degree of trust in the model outcomes. In this context, there is a growing need for data-driven technological interventions to aid scientists in comprehending how models react to both noisy and clean input variables, thus shedding light on complex behaviors and fostering confidence in the outcomes. In this paper, we present Forte, a visual analytics-based application to explore deep probabilistic net-load forecasting models across various input variables and understand the error rates for different scenarios. With carefully designed visual interventions, this web-based interface empowers scientists to derive insights about model performance by simulating diverse scenarios, facilitating an informed decision-making process. We discuss observations made using Forte and demonstrate the effectiveness of visualization techniques to provide valuable insights into the correlation between weather inputs and net-load forecasts, ultimately advancing grid capabilities by improving trust in forecasting models.
Bhattacharjee, Kaustav↗
Novel capabilities for examining and summarizing hierarchical and geographic resiliency profiles
The geospatial research and development team in the National and Homeland Security Division at Idaho National Laboratory was tasked with providing tools to derive insight from the substantial amount of data currently available - and continuously being produced - associated with the critical infrastructure of the US. This effort is in support of the Department of Homeland Security, whose mission includes the protection of this infrastructure and the enhancement of its resilience to hazards, both natural and human. We present geovisual-analytics-based approaches for analysis of vulnerabilities and resilience of critical infrastructure, designed so that decision makers, analysts, and infrastructure owners and managers can manage risk, prepare for hazards, and direct resources before and after an incident that might result in an interruption in service. Our designs are based on iterative discussions with DHS leadership and analysts, who in turn will use these tools to explore and communicate data in partnership with utility providers, law enforcement, and emergency response and recovery organizations, among others. In most cases these partners desire summaries of large amounts of data, but increasingly, our users seek the additional capability of focusing on, for example, a specific infrastructure sector, a particular geographic region, or time period, or of examining data in a variety of generalization or aggregation levels. These needs align well with tenets of in-formation-visualization design; in this paper, selected applications among those that we have designed are described and positioned within geovisualization, geovisual analytical, and information visualization frameworks.
97 MATHEMATICS AND COMPUTING↗
Opportunities and Challenges in the Visualization of Energy Scenarios for Decision-Making: Preprint
Scenario studies are a technique for representing a range of possible complex decisions through time, and analyzing the impact of those decisions on future outcomes of interest. It is common to use scenarios as a way to study potential pathways towards future build-out and decarbonization of energy systems. The results of these studies are often used by diverse energy system stakeholders - such as community organizations, power system utilities, and policymakers - for decision-making using data visualization. However, the role of visualization in facilitating decision-making with energy scenario data is not well understood. In this work, we review visualization designs employed in energy scenario studies found in the literature and publicly accessible online sources. We discuss the effectiveness of existing techniques particularly in regards to decision-making, and present opportunities and challenges in the visualization of energy system scenario data.
decision-making↗
The determination of some requirements for a helicopter flight research simulation facility
Important requirements were defined for a flight simulation facility to support Army helicopter development. In particular requirements associated with the visual and motion subsystems of the planned simulator were studied. The method used in the motion requirements study is presented together with the underlying assumptions and a description of the supporting data. Results are given in a form suitable for use in a preliminary design. Visual requirements associated with a television camera/model concept are related. The important parameters are described together with substantiating data and assumptions. Research recommendations are given.
Sinacori, J. B.↗
Man-Machine Integration Design and Analysis System (MIDAS) v5: Augmentations, Motivations, and Directions for Aeronautics Applications
As automation and advanced technologies are introduced into transport systems ranging from the Next Generation Air Transportation System termed NextGen, to the advanced surface transportation systems as exemplified by the Intelligent Transportations Systems, to future systems designed for space exploration, there is an increased need to validly predict how the future systems will be vulnerable to error given the demands imposed by the assistive technologies. One formalized approach to study the impact of assistive technologies on the human operator in a safe and non-obtrusive manner is through the use of human performance models (HPMs). HPMs play an integral role when complex human-system designs are proposed, developed, and tested. One HPM tool termed the Man-machine Integration Design and Analysis System (MIDAS) is a NASA Ames Research Center HPM software tool that has been applied to predict human-system performance in various domains since 1986. MIDAS is a dynamic, integrated HPM and simulation environment that facilitates the design, visualization, and computational evaluation of complex man-machine system concepts in simulated operational environments. The paper will discuss a range of aviation specific applications including an approach used to model human error for NASA s Aviation Safety Program, and what-if analyses to evaluate flight deck technologies for NextGen operations. This chapter will culminate by raising two challenges for the field of predictive HPMs for complex human-system designs that evaluate assistive technologies: that of (1) model transparency and (2) model validation.
Gore, Brian F.↗