Visualizing Plasma Physics Simulations in Immersive Environments

Nuno Verdelho Trindade

1 a

Oscar Amaro

2 b

, David Br

, Daniel Gonc¸alves

1 c

ao Madeiras Pereira

1 d

and Alfredo Ferreira

1 e

INESC-ID, Instituto Superior T

ecnico, University of Lisbon, Rua Alves Redol, 9, 1000-029 Lisbon, Portugal

Group of Lasers and Plasma (GoLP), Instituto Superior T

ecnico, University of Lisbon,

Complexo Interdisciplinar, Av. Rovisco Pais, 1049-001 Lisbon, Portugal

Department of Computer Science and Engineering (DEI), Instituto Superior T

ecnico, University of Lisbon,

Av. Rovisco Pais, 1, 1049-001 Lisbon, Portugal

Keywords:

Virtual Reality, Immersive Visualization, Scientiﬁc Visualization, Plasma Physics, Data Analysis.

Abstract:

Plasma physics simulations create complex datasets for which researchers need state-of-the-art visualization

tools to gain insights. These datasets are 3D in nature but are commonly depicted and analyzed using 2D

idioms displayed on 2D screens. These offer limited understandability in a domain where spatial awareness

is key. Virtual reality (VR) can be used as an alternative to conventional means for analyzing such datasets.

This study presents PlasmaVR, a proof-of-concept VR tool for visualizing datasets resulting from plasma

physics simulations. It enables immersive multidimensional data visualization of particles, scalar, and vector

ﬁelds. The study includes user evaluation with domain experts where PlasmaVR was employed to assess the

possible beneﬁts of immersive environments in plasma physics visualization. Participants manifested a high

level of engagement when using the prototype, considering it more enjoyable than conventional means. The

participant’s perception of the usefulness of VR in plasma simulations also increased after experiencing the

prototype.

1 INTRODUCTION

Plasma is a physical state of matter where a signif-

icant fraction of particles is charged (Fridman and

Kennedy, 2021). These particles, usually electrons

and ions, interact via long-range forces and sustain

rich, collective motion, waves, and instabilities (Piel,

2010). Modeling these systems requires complex

simulations that can be performed using Particle-in-

Cell (PIC) codes (Ljung et al., 2000). An example of

such a code is the fully relativistic, massively paral-

lel OSIRIS PIC code (Fonseca et al., 2002) used to

generate the data presented in this work. The datasets

obtained from these simulations consist most notably

of particle data (e.g., position, momentum, energy),

scalar ﬁeld data (e.g., energy density), and vector

ﬁeld data (e.g., electric and magnetic ﬁelds) (Fitz-

patrick, 2022). The generated datasets are 3D in

nature but commonly depicted and analyzed by re-

sorting to 2D idioms (Munzner and Maguire, 2015).

https://orcid.org/0000-0001-6621-0287

https://orcid.org/0000-0003-0615-0686

https://orcid.org/0000-0002-5121-6296

https://orcid.org/0000-0002-8120-7649

https://orcid.org/0000-0001-9278-142X

While there are applications to create and analyze

3D idioms for plasma physics (Ahrens et al., 2005;

Bethel et al., 2016), these mostly use conventional

visualization and interaction means (2D screen, key-

board, and mouse), which are not particularly engag-

ing (Guo et al., 2017). In that sense, virtual reality

(VR) can be used as an alternative to these conven-

tional means in the analysis of plasma simulations.

VR has been known to offer improved depth and spa-

tial relationship perception (Guo et al., 2022; Vienne

et al., 2020), which are fundamental for obtaining in-

sights into 3D plasma morphology. It provides a dif-

ferent perspective that results from the users’ immer-

sion in the physical constructs they are trying to ob-

serve (Millais et al., 2018). Likewise, VR can po-

tentially increase user engagement by offering more

immersive and enjoyable experiences.

This study presents PlasmaVR, a VR interactive

prototype tool to visualize the data resulting from

plasma physics simulations. The tool provides re-

searchers with an immersive environment for explor-

ing scientiﬁc datasets using natural interaction. It en-

ables multidimensional data visualization of particles,

scalar, and vector ﬁelds. The tool includes speciﬁc

functionalities for data annotation and segmentation.

Verdelho Trindade, N., Amaro, Ó., Brás, D., Gonçalves, D., Madeiras Pereira, J. and Ferreira, A.

Visualizing Plasma Physics Simulations in Immersive Environments.

DOI: 10.5220/0012357100003660

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2024) - Volume 1: GRAPP, HUCAPP

and IVAPP, pages 645-652

ISBN: 978-989-758-679-8; ISSN: 2184-4321

645

Figure 1: The immersive environment (mockup) of PlasmaVR emulates a sci-ﬁ-themed laboratory. The idiom and the slicing

planes control mechanism are visible on the right of the ﬁgure. The resulting slices are on the left of the ﬁgure.

It allows multiaxial dynamic slicing of the 3D id-

ioms with a real-time representation of corresponding

scalar 2D energy heatmaps (Figure 1).

2 RELATED WORK

Immersive technologies have been widely accepted as

an aspect of paramount relevance and a future trend

in scientiﬁc visualization (Gallagher, 2023). In that

scope, extended reality (XR) has been applied in a

wide range of domains, including in research stud-

ies related to natural, formal, and social sciences (Ko-

rkut and Surer, 2023; Mathur et al., 2023; Fombona-

Pascual et al., 2022; Yeung et al., 2021).

The application of XR technologies to plasma

physics data visualization has also been addressed in

previous research work. An example is the system

developed by Foss et al. (Foss et al., 2018), where

plasma simulation data was visualized in an aug-

mented reality (AR) environment. This work focuses

on the scalar data obtained from plasma simulations

and uses isosurfaces for its representation. The visu-

alization is presented in a time-varying format, and as

such, 3D models corresponding to the timesteps were

pre-rendered and then displayed in sequence to create

an animation. The system is limited in what concerns

interactivity, as possible user interaction mainly con-

sists of walking around the visualization. However,

researchers who tested the system found the possi-

bility of observing the isosurfaces from different per-

spectives in an AR environment very valuable. The

integration of plasma physics simulations with VR

was equally explored by Danielov

a et al. (Danielov

et al., 2019). They proposed a system that allows

researchers to visualize plasma simulation datasets.

The web-based system offers a new perspective on

complex interactions of intense laser beams with var-

ious forms of targets. It enables the analysis of parti-

cles and ﬁelds and the modiﬁcation of environmental

properties to enhance spatial features.

Ohtani et al. (Ohtani et al., 2010; Ohtani et al.,

2011b; Ohtani et al., 2011a) used a CAVE system for

visualizing plasma simulation results and device data.

They addressed the virtual representation and inter-

action with magnetic ﬁeld lines, particle trajectories,

and isosurfaces of plasma pressure. The study fo-

cused on the virtues of VR in understanding the three-

dimensional positional relationship between plasma

elements. In that scope, researchers also addressed in

a later work (Ohtani et al., 2016) how VR promoted

users’ understanding of dust particle positioning in

plasma simulation experiments. They concluded that

VR could improve understanding of the relative po-

sitional relationship between the dust particles’ tra-

jectories and the magnetic ﬁeld’s structure. In an

earlier study, Hayashi (Hayashi, 2001) had also al-

ready conceptualized how CAVE systems could be

used to simulate nonlinear phenomena in plasmas.

Ohno et al. (Ohno et al., 2006) had previously pre-

sented VFIVE, a VR visualization software for CAVE

systems, capable of representing scalar and vector

data. Lastly, the application developed by Br

as (Br

as,

2022), which was used as a base for the current study,

IVAPP 2024 - 15th International Conference on Information Visualization Theory and Applications

646

uses VR headsets in the scope of scientiﬁc visualiza-

tion of plasma physics simulations.

The present study builds upon visualization and

interaction concepts addressed in earlier work and

further explores the potential of immersive environ-

ments in plasma physics scientiﬁc visualization. In

particular, it ﬁlls in the gaps concerning the useful-

ness and usability of VR in that scope. While Foss et

al. (Foss et al., 2018) and Ohtani et al. (Ohtani et al.,

2010; Ohtani et al., 2011b; Ohtani et al., 2011a)

used CAVE and AR systems, we set out to ﬁnd out

how a system capable of a potentially more immer-

sive experience (designed for VR headsets) could per-

form in that sense. Also, unlike the study conducted

by Foss et al. (Foss et al., 2018), we used an inter-

face with integrated analytics features. These features

share some of the characteristics of the work devel-

oped by Danielov

a et al. (Danielov

a et al., 2019) but

were designed natively for VR interaction instead of

the web interface proposed by these researchers.

3 SYSTEM OVERVIEW

PlasmaVR is an interactive tool for scientiﬁc visu-

alization and exploration of datasets that result from

plasma physics simulations in an immersive environ-

ment. The tool was born from the need of the Group

of Lasers and Plasma (GoLP) (at Instituto Superior

ecnico (IST), University of Lisbon) researchers to

have an improved depth and spatial relationship per-

ception when analyzing 3D plasma idioms. The

general requirements for PlasmaVR were established

from interviews with these researchers. They in-

cluded animated visualization of the changing dy-

namics of the simulated systems (particle positions,

scalar ﬁelds, and vector ﬁelds - Figure 2) and play-

back control over these animations. They also in-

cluded the ability to perform dynamic time-dependent

annotation and slice and segment the 3D idioms into

2D energy heatmaps.

The system aggregates two complementary mod-

ules: the data processing and VR modules. The ﬁrst

aims to process the high volume of raw data from

plasma simulation experiments. This raw data is gen-

erated in the HDF5 (The HDF Group, 2007) format,

and the processing module transforms it into a model

that can be used inside the graphical engine (Unity).

This module can process point clouds as well as scalar

and vector volumes. The second module handles the

representation of the different virtual elements inside

the immersive environment and the user interaction.

When the users put on their VR headsets, they are

inserted into an environment that simulates a sci-ﬁ

laboratory-themed room. This virtual room is where

the plasma exploration takes place (Figure 1). In the

center, the chosen type of plasma structure ﬂuctuates

above a platform and can be animated, rotated, re-

sized, sectioned, or annotated. The user can move

around the room, enter inside the plasma structure,

slice it, and observe the intricacies of its morphology.

PlasmaVR uses a ﬂoating panel (which can be

shown or hidden) attached to the left VR controller to

access the different features. It includes buttons that

lead to the playback control, slicing, rotation/resizing

features, annotation, and the immersive environment

conﬁguration. The ﬁrst of these features is the play-

back control, which incorporates play/pause buttons

and a timeline. This timeline can be used to jump to

a speciﬁc frame in the idiom’s animation or observe

step-by-step modiﬁcations of the plasma structure.

When analyzing the idioms, the users can rotate

and resize them to view the data from different an-

gles and perspectives. The rotation of the idioms is

performed with a mapping to the controllers’ motion.

When the rotation mode is activated, a virtual model

of a hand holding a sphere appears in place of the

model of a standard controller. This sphere works as a

’proxy’ for the 3D idiom. The user can then press the

controller trigger to grab the sphere and rotate it with

their virtual hand. The idiom follows the sphere’s ro-

tation with three degrees of freedom.

Figure 2: Particles (left), streamlines (center), and isosurfaces (right) idioms represented in the immersive environment and

corresponding symbols used in the interface (top-right corners).

Visualizing Plasma Physics Simulations in Immersive Environments

647

PlasmaVR also includes a slicing feature, which is

directed at producing formal results of data analysis.

To extract the slices, the users can move small spher-

ical handles attached to each axis of the 3D plasma

idiom. These handles are, in turn, linked to planes

that bisect the idiom and will move along its respec-

tive axis. The position of each plane determines the

sections that will be extracted (Figure 3). A 2D panel

displays the heatmaps corresponding to the bisection

from the three planes. This real-time multiaxial rep-

resentation of energy heatmaps allows the researchers

to document how the values change inside the repre-

sented ﬁelds.

When analyzing a plasma idiom, researchers may

want to highlight speciﬁc aspects of what is happen-

ing in the simulation. However, annotating some-

thing in a 3D idiom using a keyboard, mouse, and 2D

screen may be tedious and counterintuitive. Thus, re-

searchers usually either make 2D annotations or gen-

erate and move 3D objects (e.g., arrows) to the area

they want to highlight. On the contrary, 3D annota-

tion ﬁts particularly well within the PlasmaVR en-

vironment and interaction. The annotation feature

takes advantage of VR’s increased depth and spa-

tial relationship perception. The researcher can enter

inside the plasma structure and make geometrically

complex and precise 3D annotations, thus highlight-

ing valuable simulation insights. Due to the ability

to draw freely in 3D, it is easy to draw annotations

like in Figure 4 (right), where the purple annotation

wraps around a volumetric protuberance in the struc-

ture, thus providing information more comprehen-

sively. The annotations can be aggregated in groups,

and their colors can be customized using the annota-

tions menu (Figure 4, left), accessible from the main

panel. This feature is also adapted to the dynamic na-

ture of the plasma idiom. Because the plasma struc-

ture representation changes with time, the users can

select a speciﬁc time frame where the annotation will

be visible. This possibility allows researchers to make

dynamic annotations that track, for example, the path

of a particular anomaly as the plasma animation pro-

gresses.

4 EVALUATION

Domain experts from GoLP interacted with the ap-

plication and performed a set of predeﬁned tasks. An

array of objective metrics was recorded during this in-

teraction. They were then asked to answer question-

naires concerning the prototype’s usability and use-

fulness. This section details how that evaluation was

carried out.

4.1 Methodology

The study was conducted with an experimental group

of ﬁve domain experts, from which informed consent

was obtained. As plasma researchers, the participants

were ideal to measure the possible beneﬁts of Plas-

maVR in the visualization of the data resulting from

plasma physics simulations. The hardware consisted

of an Oculus Quest 2 VR headset with a pair of con-

trollers. The headset was connected to a desktop com-

puter with an Intel Core i7-8700 CPU @ 3.20GHz

processor, 16GB of RAM, and a NVIDIA GeForce

GTX 1060 3GB graphics card. A monitor, keyboard,

and mouse were also used (for ﬁlling out question-

naires).

The participants were asked to perform a set of

three tasks that were designed to be realistic and, at

the same time, would allow them to have contact with

the extended scope of the prototype’s functionalities.

In the ﬁrst task, the participants were required to draw

a wide circle of a speciﬁc color surrounding a pre-

drawn isosurface idiom and then deﬁne a time inter-

val for when the annotation would be visible in the

Figure 3: The three intersecting planes can be moved along its axis to generate the corresponding slices. In the example of

the ﬁgure, moving the handle of the horizontal plane up the YY axis (red arrow and small red circle) results in the real-time

update of the corresponding energy heatmap for the XZ slice (large red circle).

IVAPP 2024 - 15th International Conference on Information Visualization Theory and Applications

648

Figure 4: The annotations menu allows users to deﬁne its characteristics, including the range of animation frames where they

will be shown (left). Users can do 3D annotations to highlight relevant portions of the idioms (right) (Br

as, 2022, p. 35).

simulation. This task was aimed at testing the an-

notation and the corresponding timeline performance.

Namely, it was introduced to assess the spatial percep-

tion within the immersive environment by testing how

easy and intuitive it was to use the annotation tool to

draw in space. It equally allowed the assessment of

how the participants would perform in changing the

color of an annotation element and specifying a time-

line interval within the simulation using the interface

panels.

For the second task, the participants were asked

to rotate the isosurface to have the y-axis pointing to-

wards the right. This more straightforward task was

aimed at testing the rotation functionality’s perfor-

mance. In particular, in assessing how the proxy ro-

tation would perform in terms of precision in rela-

tion to the VR controller’s movement. This perfor-

mance would indicate how well the rotation mecha-

nism transmitted depth perception to the user.

In the third task, the participants were asked to

ﬁnd the portion of an isosurface with the lowest

charge density value. This task was designed to as-

sess the analytics performance of the prototype. It

required participants to use the slicing tool to extract

the energy heatmaps to be able to ﬁgure out the por-

tion with the lower density. Such a sequence of op-

erations adequately estimated how well spatial rela-

tionship was perceived in the isosurface visualization.

Likewise, it provided a good indicator of how well

users can match this 3D visualization of data with

the 2D representation in slices. After completing the

three tasks, the participants were asked to complete

a 10-item System Usability Survey (SUS) (Brooke,

1995) questionnaire.

4.2 Results and Discussion

The group of ﬁve participants was composed of re-

searchers with ages ranging from 18-50 years old.

All had experience with plasma simulations and

OSIRIS/PiC Codes (20% more than ﬁve years, 60%

between one and ﬁve years, and 20% less than one

year experience). Most (80%) had earlier experience

with using VR technologies.

To assess the suitability of the prototype for dif-

ferent types of tasks, a set of objective metrics, such

as completion time and number of errors, were ana-

lyzed. Regarding the time participants took to com-

plete each task type (annotation, rotation, and slic-

ing, as described in the previous section), the rota-

tion task corresponded to a shorter (mean time in min-

utes ± standard error) completion time (1.32 ± .153)

when compared to annotation (2.87 ± .321) and slic-

ing (3.50 ± .224).

While the slicing task had a marginally higher

completion time, it corresponded to a much lower

(mean number of errors ± standard error) number of

mistakes (0.60 ± .179) than the annotation task (1.80

± .219). This difference may indicate that the pro-

totype is better ﬁtted to handle analytics tasks than

annotation tasks. The rotation task had similar errors

(0.60 ± .110) to the slicing task.

To assess the usability of PlasmaVR, the partic-

ipants were asked to complete a ten-question stan-

dard SUS questionnaire with a ﬁve-level Likert scale

for agreement (1: Strongly disagree and 5: Strongly

agree) after interacting with the prototype. An aver-

age SUS score of 75.5 (SD = 5.5) was obtained. Such

a score can be paired with a rating of ’Good’ (Bangor

et al., 2009) or ’B’ (74.1 - 77.1) (Lewis and Sauro,

2017). Although the small number of participants im-

pacts the accuracy of the usability evaluation (< 35%

accuracy, based on the sample size threshold proposed

Visualizing Plasma Physics Simulations in Immersive Environments

649

by Tullis and Stetson (Tullis and Stetson, 2004)), the

majority had a positive perception and found the sys-

tem usable.

We also wanted to identify the speciﬁc aspects

where the system performed well and where it could

be enhanced in the scope of future development ef-

forts. With that objective, the SUS questions were

broken down into eight categories. These reﬂect the

different usability areas that were addressed. The cat-

egories include cohesiveness (how well-integrated the

prototype’s features are), learnability (how easily it

can be learned), and intuitiveness (how simple and

easy to use). They also include concision (how un-

complicated the interface is), reliability (how few in-

consistencies are in the prototype), and comfort (how

non-frustrating its use is). Furthermore, they include

trustworthiness (how conﬁdent participants were us-

ing the prototype) and usage intention (how much par-

ticipants expected to use it). Results show that the

aspects that performed better (mean (standard error);

median (interquartile range) for the SUS score) were

cohesiveness (3.40 (.110); 3.00 (1.00)), learnability

(3.33 (.067); 3.33 (0.67)), intuitiveness (3.20 (.167);

3.00 (1.00)), concision (3.20 (.167); 3.00 (1.00)), and

reliability (3.20 (.089); 3.00 (0.00)). Aspects that per-

formed below average include comfort (2.80 (.089);

3.00 (0.00)) and trustworthiness (2.60 (.110); 3.00

(1.00)). The lowest contribution came from usage in-

tention (1.80 (.089); 2.00 (0.00)). These results are

illustrated in Figure 5.

The results are mainly within a relatively narrow

range. The aspects that performed better are those

related to the overall experience with the prototype

and how simple and easy the system is to use. Par-

ticipants found the interface reliable, well-structured,

and cohesive. A good level of learnability was also

observed, which seems to be a direct consequence of

how intuitive the participants considered the interface.

Figure 5: Distribution of participant’s score for each usabil-

ity category.

These results align with the participants’ increased

perception of the usefulness of VR after testing the

prototype, which will be addressed further.

Nevertheless, participants found that while the

prototype was reliable, they did not feel entirely con-

ﬁdent using it. This apparent contradiction might be

justiﬁable by interaction limitations pointed out by

participants (e.g., difﬁculties in doing a full rotation

of the idiom using a single controller motion, which

will be discussed later). The most unexpected result,

however, was the one corresponding to usage inten-

tion, which achieved the lowest score of all categories.

This lower classiﬁcation might result from the more

localized role in their workﬂow that some researchers

identiﬁed as the main scope of the prototype. More

speciﬁcally, some participants positioned its useful-

ness in a faster preliminary visualization of the plasma

physics data as a ﬁrst step before moving to a more

exhaustive analysis using conventional means.

Additionally, we wanted to determine if the partic-

ipant’s perception of the usefulness of VR in plasma

simulations had changed after experiencing the pro-

totype. Before using the prototype, the participants

were divided on the usefulness of VR in plasma sim-

ulations. Indeed, only 40% agreed that VR would be

useful in helping their workﬂow, 20% neither agreed

nor disagreed, and 40% disagreed (ﬁve-level Lik-

ert scale for agreement, 1: Strongly disagree and 5:

Strongly agree). After using the prototype, partici-

pants’ perception changed to much more positive val-

ues, with 60% strongly agreeing on the usefulness of

VR in plasma simulations, 20% agreeing, and 20%

neither agreeing nor disagreeing. This substantial

shift in opinion regarding the usefulness of VR in

plasma simulations suggests that the user experience

with the prototype was impactful and meaningful to

the participants. As such, it is consistent with a high

level of engagement despite the lower usage intention

previously addressed.

We also enquired users about the aspects of the

prototype they thought would contribute to mak-

ing VR application useful in their workﬂow. 20%

strongly agreed, and 80% agreed that VR could be

used to display data effectively. 60% strongly agreed,

20% agreed, and 20% neither agreed nor disagreed

that VR was useful for highlighting relevant informa-

tion. 20% strongly agreed, 40% agreed, 20% neither

agreed nor disagreed, and 20% disagreed that VR im-

proved the data exploration experience. Lastly, 80%

strongly agreed, and 20% agreed that VR was a more

enjoyable way of exploring plasma simulation data

than conventional means. It’s worth highlighting that

the highest of these scores corresponds to the way par-

ticipants found PlasmaVR enjoyable, which is, once

IVAPP 2024 - 15th International Conference on Information Visualization Theory and Applications

650

again, compatible with a high level of engagement.

4.3 Limitations and Future Work

When analyzing the results from this work, the ratio-

nale behind a few methodological decisions and their

corresponding limitations should be considered. The

ﬁrst of these limitations is the small sample size used

in the study, which makes it harder to assert statisti-

cal signiﬁcance. In that sense, the study could have

been carried out with more participants by extending

the sample selection to encompass non-expert users

or physics researchers from areas other than plasmas.

We chose instead to restrict the sample selection to

domain experts, which allowed us to ensure a consis-

tent baseline among the participants regarding plasma

experiments data analysis knowledge. Likewise, we

opted for using a more controlled experimental envi-

ronment instead of, e.g., making the application avail-

able online and asking users to download and execute

the application by themselves.

Another methodological issue that limits the scope

of this study is the absence of a comparative as-

sessment of conventional analysis means with VR,

namely by using an experimental control group. As

such, assumptions regarding improvements in perfor-

mance or usability can only be substantiated by par-

ticipants’ feedback (collected using questionnaires)

and not by differences in measured performance met-

rics. Nevertheless, while not in the scope of this study,

such comparative assessment can be addressed in fu-

ture work.

There are several opportunities to expand this

study beyond its current scope. Potential future re-

search directions may include overcoming some of

the limitations mentioned above. Such improvements

may mean extending the experimental group to in-

clude researchers from plasma physics research units

other than GoLP. They may also imply, e.g., the

comparison of PlasmaVR with augmented reality and

desktop versions of the prototype to further assess

the advantages and limitations of immersive environ-

ments in plasma physics simulations.

5 CONCLUSION

This work presents a novel prototype tool for visual-

izing plasma physics experiment datasets in VR. The

tool enables a multidimensional data visualization en-

vironment where users can travel around and inside

animated representations of plasma based on time-

dependent data. It allows them to observe the struc-

tural variations in morphology over time from several

points of view. The work shows the different char-

acteristics of the tool, including its architecture, raw

data processing capabilities, and user interface func-

tionalities. It addresses its evaluation with a group

of domain experts consisting of plasma physics re-

searchers. This evaluation is carried out using a set

of objective and subjective metrics. These metrics are

collected during testing through direct measurement

and after testing using questionnaires. The collected

metrics are used to support the research questions,

which aim to ascertain the usability and usefulness of

VR in plasma physics visualization. The ﬁndings sug-

gest that applying VR technologies to plasma physics

visualization can result in a usable experience. The

results also support the hypothesis that VR can be use-

ful in plasma physics visualization.

ACKNOWLEDGEMENTS

This work was supported by national funds

through FCT, Fundac¸

ao para a Ci

encia e a

Tecnologia, under project UIDB/50021/2020

(DOI:10.54499/UIDB/50021/2020) and under grants

2021.07266.BD and UI/BD/153735/2022. The

funding sources had no involvement in study design;

in the collection, analysis, and interpretation of data;

in the writing of the report; or in the decision to

submit the article for publication. This paper uses

the work of Br

as (Br

as, 2022) as a base and expands

it by considering additional factors and conducting

substantively different assessments.

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