Scientific Visualization Tools Research Articles

VISUALIZATION OF TURBULENT EVENTS VIA VIRTUAL/AUGMENTED REALITY

Mixed reality technology, i.e., virtual (VR) and augmented (AR) reality, has spread from research laboratories to enter the homes of many. Further, the widespread adoption of these technologies has caught the scientific community's attention, which is constantly researching potential applications. Backed by the continued enhancement of high-performance computing in hardware and software, we are applying mixed reality technologies as a scientific visualization tool for fluid dynamics purposes. In particular, we show a virtual wind tunnel (along with the simplified methodology to replicate it) that enables the user to visualize complex and intricate turbulent flow patterns within an immersive environment. Briefly, high spatial/temporal resolution numerical data over supersonic turbulent boundary layers subject to concave and convex wall curvature has been creatively "pipelined" for VR/AR visualization via several scripts, software, and apps, which are further explained and described along the manuscript. The intention is to present a technique of how to visualize fluid flows to be the most convenient for the user, especially if one is slightly unfamiliar with scientific visualization. Whereas VR/AR applications are principally discussed here for flow visualization, the lessons learned can be certainly extended to other disciplines involving three-dimensional time-dependent databases.

Role of Green Finance for Sustainable Environment So Far: A Bibliometric Analysis and Policy Framework

A bibliometric examination of green finance's contribution to environmental sustainability is the intended outcome of this work. The research also offers a policy framework for environmentally friendly financing. To produce the bibiometric analysis, we used proper keywords to sift through the Scopus database for relevant, peer-reviewed research articles published between 2008 and 2022 (Dec 2022). In this study, the titles, abstracts, keywords, frameworks, and headers of 444 relevant papers were screened using bibliographic coupling and text mining. The research used the scientific landscapes visualization tool for the analysis. Our evaluation provides a systematic account of the effectiveness of related works in the field of green finance. Authors, publications, and theoretical and topical contributions to the field are all revealed through bibliometric analysis. This paper provides a theoretical framework for future studies on the effects of green financing on sustainable environments. The interdependencies between different industries and how they might work together to protect the environment are also laid forth. Green finance plays a unique role in protecting the natural world. This work makes a contribution to the literature on green finance and sustainable environments by identifying theoretical clusters for future research on environmental performance. The paper also lays out the goals of the green finance policy framework.

How to Improve Utilizing Neural Interface by Means of Ontology-Driven Scientific Visualization Tools

How to Improve Utilizing Neural Interface by Means of Ontology-Driven Scientific Visualization Tools

Clustering-informed cinematic astrophysical data visualization with application to the Moon-forming terrestrial synestia

Scientific visualization tools are currently not optimized to create cinematic, production-quality representations of numerical data for the purpose of science communication. In our pipeline Estra, we outline a step-by-step process from a raw simulation into a finished render as a way to teach non-experts in the field of visualization how to achieve production-quality outputs on their own. We demonstrate feasibility of using the visual effects software Houdini for cinematic astrophysical data visualization, informed by machine learning clustering algorithms. To demonstrate the capabilities of this pipeline, we used a post-impact, thermally-equilibrated Moon-forming synestia from Lock et al., (2018). Our approach aims to identify “physically interpretable” clusters, where clusters identified in an appropriate phase space (e.g. here we use a temperature–entropy phase–space) correspond to physically meaningful structures within the simulation data. Clustering results can then be used to highlight these structures by informing the color-mapping process in a simplified Houdini software shading network, where dissimilar phase–space clusters are mapped to different color values for easier visual identification. Cluster information can also be used in 3D position space, via Houdini’s Scene View, to aid in physical cluster finding, simulation prototyping, and data exploration. Our clustering-based renders are compared to those created by the Advanced Visualization Lab (AVL) team for the full dome show “Imagine the Moon” as proof of concept. With Estra, scientists have a tool to create their own production-quality, data-driven visualizations.

Motivations, design, and preliminary testing for a 360° vision simulator

Contemporary virtual reality systems enable academics to more efficiently explore and analyze complex three-dimensional (3D) content, but their utility is limited by visual short-term memory. Janus, a geometry agnostic shader script, circumvents this cognitive limitation by automatically rendering complex object meshes to fit entirely within the field-of-view of consumer head-mounted displays. The resulting 360° vision experience represents an advantage over existing scientific data visualization tools, which have sought to replicate real-world viewing experiences but have inadvertently replicated associated limitations as well. By presenting data in such a way so as to effectively circumvent cognitive loads associated with body (or object) movement, academics can use the Janus shader to more readily engage in the exploratory analysis of complex 3D data sets, thereby facilitating scientific insight. This paper explores the motivations and design of the Janus shader and describes preliminary results from user testing conducted under controlled conditions. For the 24 study participants (N = 24), statistically significant time-to-completion decreases were observed for spatial analysis tasks taking place in intervention (Janus-enabled) VR scenes of low-to-moderate complexity.

Аpplication of scientific visualization tools in the study of supersonic vortex pair

Аpplication of scientific visualization tools in the study of supersonic vortex pair

클러스터 기반 과학적 가시화 도구를 위한 가시화 파이프라인 설계 및 구현

본 논문은 클러스터 기반 과학적 가시화 도구를 위한 가시화 파이프라인의 설계를 제안하고 그 구현 사례를 공유한다. 본 연구의 파이프라인은 각각의 가시화 기법을 표현하는 가시화 파이프들로 구성되며, 가시화 파이프들은 정형화된 파이프 구조를 사용함으로서 상호 유연한 연결을 보장한다. 또한 파이프라인을 사용하는 가시화 도구와 통신을 전담하는 특수 파이프(인터페이스 파이프)를 사용함으로서, 가시화 도구에 독립적인 구현 및 관리가 가능하다. 제안된 가시화 파이프라인은 인터페이스 파이프들을 제외한 하위 파이프라인을 각 연산 노드에 배치하고, 이들을 마스터 노드에 있는 인터페이스 파이프에 연결함으로서 클러스터 기반 가시화 파이프라인으로 간단히 확장된다. 파이프라인은 사용자의 가시화 요청을 처리할 수 있는 파이프의 조합으로 실시간으로 생성된다. 본 연구는 제안하는 가시화 파이프라인을 클러스터 기반 가시화 프레임워크 중 하나인 GLOVE를 기반으로 32개의 연산노드로 구성된 클러스터에 구현하였으며, 네 종류의 대용량 과학데이터의 가시화에 적용하였다. 그 결과 다양한 조합의 가시화 요청을 성공적으로 처리하였으며, 연산 노드 수 증가에도 안정적으로 동작하는 모습을 확인 할 수 있었다. 또한 동일한 조합의 가시화 요청에 대해, 파이프라인을 적용하기 전 GLOVE 대비 최대 7.72배 높은 가시화 성능을 보여주었다. 이는 제안한 가시화 파이프라인의 효용성 및 확장성을 보여주는 결과다.

Capturing the dance of the earth: PolarGlobe: Real-time scientific visualization of vector field data to support climate science

This paper introduces a streamline visualization technique that empowers PolarGlobe, an interactive, virtual globe-based, multi-dimensional scientific visualization tool to facilitate the observation and visual inspection of changes in the climate in real time. Specifically, this technique achieves effective visualization of vector-based earth science data through an automated data processing pipeline which integrates novel strategies including random seeding, finer-granularity parallelization and real-time rendering. The random seeding strategy allows for a vivid visual effect and an interactive framerate regardless of the spatial resolution in the raw dataset. The visualization algorithm is designed to be naturally parallelizable by partitioning the rendering tasks of unsteady vector field into multiple subtasks such that high-performance rendering can be realized. The platform is capable of taking either irregular or regular gridded data as input, and through the proposed data (re)projection pipeline, an automatic transformation of spatially enabled scientific data from the original data projection to the 3D globe-based virtual space is achieved. A series of experiments was conducted to identify the best configuration of rendering parameters to achieve the optimal rendering performance and visual effect. The results demonstrated the scalability and capability of the proposed PolarGlobe system to visualize big and unsteady vector flow data across different spatial and temporal scales. PolarGlobe implements former Vice President Al Gore's vision of a digital earth that enables scientists and citizens across the world to interactively study our planet. We expect the methods and techniques presented in this work to contribute significantly to both the scientific visualization and climate science communities.

Visualizing the landscape and evolution of leadership research

Complementing prior quantitative and qualitative reviews of the leadership literature, we conduct a bibliometric analysis of leadership articles. Our bibliometric review provides a different perspective by portraying the landscape and developmental trajectory of leadership research over time via co-citation and co-occurrence analyses. Using a scientific visualization tool CiteSpace and 6528 leadership works collected from the Web of Science database from 1990 to 2017, we detect and visualize the landscape of leadership research and track how this landscape has evolved. After mapping the landscape, we discuss the insights gleaned from our bibliometric review, with a focus on open questions, future research directions, and implications. In doing so, our review provides readers with a systematic understanding of the development of the leadership field and a roadmap to spark leadership research and move this literature forward.

πScope: Python based scientific workbench with MDSplus data visualization tool

A newly developed python based scientific data analysis and visualization tool, πScope (http://piscope.psfc.mit.edu), is reported. The primary motivation is 1) to provide an updated tool to browse the MDSplus data beyond existing dwscope/jScope and 2) to realize a universal foundation to construct interface tools to perform computer modeling from experimental data. To visualize MDSplus data, πScope has many features including overplotting different signals and discharges, generating various plot types (line, contour, image, etc.), performing in-panel data analysis using python scripts, and producing publication quality graphics. The logic to generate multi-panel plots is designed to be backward compatible with dwscope, enabling smooth migration for users. πScope uses multi-threading in data loading, and is easy to modify and expand due to its object-oriented design. Furthermore, A user can access the data structure both from a GUI and a script, enabling relatively complex data analysis workflow built quickly on πScope.

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multi-phase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations and probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound-bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.

Using Scientific Visualization Tools to Bridge the Talent Gap

Abstract In this paper the use of adaptive scientific visualization tools in education, including in the area of high performance computing education is proposed in order to help students understand in depth the nature of particular scientific problems and to help them to learn parallel computing approaches to solving these problems. The proposed approach may help to bridge the talent gap in natural and computational sciences, since high quality visualization can help to uncover hidden regularities in the data with which the researchers and students work and can lead to new level of understanding how the data can be partitioned and processed in parallel. A multiplatform client-server scientific visualization system is presented that can be easily integrated with third-party solvers from any field of science. This system can be used as a visual aid and a collaboration tool in high performance computing education.

MagHD: a new approach to multi-dimensional data storage, analysis, display and exploitation

The ever increasing amount of data and processing capabilities – following the well- known Moore's law – is challenging the way scientists and engineers are currently exploiting large datasets. The scientific visualization tools, although quite powerful, are often too generic and provide abstract views of phenomena, thus preventing cross disciplines fertilization. On the other end, Geographic information Systems allow nice and visually appealing maps to be built but they often get very confused as more layers are added. Moreover, the introduction of time as a fourth analysis dimension to allow analysis of time dependent phenomena such as meteorological or climate models, is encouraging real-time data exploration techniques that allow spatial-temporal points of interests to be detected by integration of moving images by the human brain. Magellium is involved in high performance image processing chains for satellite image processing as well as scientific signal analysis and geographic information management since its creation (2003). We believe that recent work on big data, GPU and peer-to-peer collaborative processing can open a new breakthrough in data analysis and display that will serve many new applications in collaborative scientific computing, environment mapping and understanding. The magHD (for Magellium Hyper-Dimension) project aims at developing software solutions that will bring highly interactive tools for complex datasets analysis and exploration commodity hardware, targeting small to medium scale clusters with expansion capabilities to large cloud based clusters.

3D geospatial modelling and visualization for marine environment: Study of the marine pelagic ecosystem of the south-eastern Beaufort Sea, Canadian Arctic

Abstract. Geospatial modelling of the marine pelagic ecosystem is challenging due to its dynamic and volumetric nature. Consequently, conventional oceanographic spatial analysis of this environment is in a 2D environment, limited to static cutting planes in horizontal and vertical sections to present various phenomena. In this paper, we explore the contribution of recent 3D development in GIS and in scientific visualization tools for representation and analyses of oceanographic data sets. The advantages of a 3D solution are illustrated with a 3D geospatial voxel representation of water masses distribution in the southeastern Beaufort Sea (west of the Canadian Arctic).

Visualizing a Journal that Serves the Computational Sciences Community

Let's face it: The printed journal format that has served the scientific research community satisfactorily for more than 200 years doesn't serve the computational sciences community well at all. The community should, instead, communicate and archive the results of its research endeavors through a venue that lets students and colleagues fully examine published computational results and critique the numerical algorithms the authors used to generate them. A suitable computational sciences journal must principally reside in the digital rather than hardcopy world and, we propose, should consist of an interactive scientific visualization tool that is fully embedded within a versatile Wiki. The basic framework for such a journal already exists within the open source community. As we show here, for example, the SCI Institute's VisTrails Wiki (www.vistrails.org) provides many features that would be desirable in an interactive, visual, and archival computational sciences journal. It's impossible to effectively illustrate the advantages of an interactive, visual, and archival journal (IVAJ) over a traditional journal through a CiSE Visualization Corner article, which itself is intended principally to appear in print. Hence, to fully engage in this discussion, we encourage readers to interact with an article that we've posted in a proposed IVAJ format. We provide instructions for that interaction here; you can also find an abbreviated set of instructions at www.vistrails.org/index.php/ UserTbhline/IVAJ. Another useful reference is our May/June 2009 Visualization Corner article.1 Here we demonstrate how an IVAJ can help that published article's printed pages come alive and can considerably expand on its basic scientific content.

Spatial input for temporal navigation in scientific visualizations.

Scientific-visualization tools can make time-varying simulations easier to understand. The growing efficiency of today's high-performance computers enables simulation of physical phenomena with a high temporal resolution. Consequently, visualization systems require efficient navigation in the temporal dimension. This 3D user interface employs direct-manipulation metaphors for temporal navigation in scientific visualizations. By interacting with objects using their 3D trajectory, users can navigate in time by specifying spatial inputs.

CAD and CAE Integration Through Scientific Visualization Techniques for Illumination Design

Engineers tend to use different software to perform tasks such as geometry modeling, database management, numerical analysis, and visualization. This may cause decrease of productivity and loss of information during the conversion process between different data file formats. This paper presents a computer aided design (CAD) and computer aided engineering (CAE) system integration using scientific visualization tools and techniques. It deals with the development of a 3D CAD add-in for lighting analysis which uses the CAD model as 3D interface for creating a lighting scheme, processing, and visualizing 2D or 3D illuminance fields. Visualization features as color and contour mapping were developed using the visualization toolkit (VTK) toolkit. The application integrates all functionalities of the 3D CAD with tools for light sources database management, pre-processing, processing, and post-processing of illuminance fields in a single environment. This approach increases productivity and eliminates the need for different software.

Topological Landscapes: A Terrain Metaphor for Scientific Data

Scientific visualization and illustration tools are designed to help people understand the structure and complexity of scientific data with images that are as informative and intuitive as possible. In this context the use of metaphors plays an important role since they make complex information easily accessible by using commonly known concepts. In this paper we propose a new metaphor, called "Topological Landscapes," which facilitates understanding the topological structure of scalar functions. The basic idea is to construct a terrain with the same topology as a given dataset and to display the terrain as an easily understood representation of the actual input data. In this projection from an $n$-dimensional scalar function to a two-dimensional (2D) model we preserve function values of critical points, the persistence (function span) of topological features, and one possible additional metric property (in our examples volume). By displaying this topologically equivalent landscape together with the original data we harness the natural human proficiency in understanding terrain topography and make complex topological information easily accessible.

Zherlock: An Open Source Data Analysis Software

Zherlock is an open source software that provides state-of-the-art data analysis tools to the user in an intuitive and flexible way. It is a front-end to different numerical “engines” to produce a seamless integration of algorithms written in different computer languages. Of particular interest is creating an interface to high-level scientific languages such as Octave (a Matlab clone) and R (an S-PLUS clone) to enable efficient porting of new data analytical methods. Zherlock uses advanced scientific visualization tools in 2-D and 3-D and has been extended to work on virtual reality (VR) systems. Central to Zherlock is a visual programming environment (VPE) which enables diagram based programming. These diagrams consist of nodes and connection lines where each node is an operator or a method and lines describe the flow of data between nodes. A VPE is chosen for Zherlock because it forms an effective way to control the processing pipeline in complex data analyses. The VPE is similar in functionality to other programs such as IRIS Explorer, AVS or LabVIEW.

Using scientific visualization tools to facilitate analysis of multi-dimensional data from a spatially explicit, biophysical, individual-based model of marine fish early life history

Megrey, B. A., Hinckley, S., and Dobbins, E. L. 2002. Using scientific visualization tools to facilitate analysis of multi-dimensional data from a spatially explicit, biophysical, individual-based model of marine fish early life history. – ICES Journal of Marine Science, 59: 203–215. Individual-based models (IBM), as an ecological modeling paradigm, are being used widely in the analysis of fish populations in marine ecosystems. The flexibility and power of IBMs with respect to building detailed and realistic biological models have encouraged recent and important extensions, which include explicit spatial dynamics and biophysical forcing of certain life stage processes. Unfortunately, the usefulness of individual-based numerical simulation models is often negated by the difficulty in digesting and analyzing their voluminous and complicated output. Scientific visualization tools offer the capability to remedy this problem. In this paper we briefly describe our spatially explicit, biophysical, individual-based model, its data input and output characteristics and the off-the-shelf visualization tools we used to help facilitate analysis and interpretation of the model. A stand-alone, easy-to-use, post-processing, graphic user interface is described that permits rapid examination and integrated visualization of multi-dimensional model output. Specific examples are provided showing how scientific visualization, as a research tool, provided valuable assistance in untangling complex model dynamics, assisted with diagnostic analyses related to model validation, helped investigate trends, and apparent oddities in the data, and facilitated the communication of model results.