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DOE OSTI2024

Introducing NOODLES: Collaborative Visualization in a Flavorful Package

We introduce NOODLES, a lightweight collaborative visualization and analysis protocol. NOODLES was developed to enable new scientific workflows while enhancing existing pipelines. Using a technology-minimal approach to strengthen applicability, this protocol allows researchers to tie disparate software together as well as making domain specific visualizations accessible across various platforms and form factors. In this talk we discuss background, challenges, and gaps in the current tool landscape that lead to the development of the protocol. We then describe the design of the protocol and present several use cases to demonstrate the efficacy of NOODLES in addressing complex visualization challenges and how it co-exists with existing tools. We conclude by outlining in-progress work and potential avenues for future development within the NOODLES framework.

collaborative analysis↗
DOE OSTI2024

Involving the new generations in Fermilab endeavors

Since 1984 the Italian groups of the Istituto Nazionale di Fisica Nucleare (INFN) and Italian Universities, collaborating with the DOE laboratory of Fermilab (US) have been running a two-month summer training program for Italian university students. While in the first year the program involved only four physics students of the University of Pisa, in the following years it was extended to engineering students. This extension was very successful and the engineering students have been since then extremely well accepted by the Fermilab Technical, Accelerator, and Scientific Computing Division groups. Over the many years of its existence, this program has proven to be the most effective way to engage new students in Fermilab endeavors. Many students have extended their collaboration with Fermilab with their Master’s Thesis and PhD. Since 2004 the program has been supported in part by DOE in the frame of an exchange agreement with INFN. Over its almost 40 years of history, the program has grown in scope and size and has involved more than 550 Italian students from more than 20 Italian Universities, Several Institutes of Research, including ASI and INAF in Italy, and the ISSNAF Foundation in the US, have provided additional financial support. Since the program does not exclude appropriately selected non-Italian students, a handful of students from European and non-European Universities were also accepted over the years. Each intern is supervised by a Fermilab Mentor responsible for performing the training program. Training programs spanned from Tevatron, CMS, Muon (g-2), Mu2e, and Short Baseline Neutrino Experiments and DUNE design and experimental data analysis, development of particle detectors (silicon trackers, calorimeters, drift chambers, neutrino and dark matter detectors), design of electronic and accelerator components, development of infrastructures and software for exascale data handling, research on superconductive elements and on accelerating cavities, and theory of particle accelerators. Since 2010, within an extended program supported by the Italian Space Agency and the Italian National Institute of Astrophysics, a total of 30 students in physics, astrophysics, and engineering have been hosted for two months in the summer at US space science Research Institutes and laboratories. In 2015 the University of Pisa included these programs within its educational programs. Accordingly, Summer School students are enrolled at the University of Pisa for the duration of the internship and are identified and ensured as such. At the end of the internship, the students are required to write summary reports on their achievements. After positive evaluation by a University Examining Board, interns are acknowledged credits for their Diploma Supplement. The program was canceled in 2020 and 2021 due to the pandemic but restarted successfully in 2022. We believe this program can be taken as a model and easily adopted by interested institutions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2026

Self-Admitted Technical Debt in Scientific Software: Prioritization, Sentiment, and Propagation Across Artifacts

Self-admitted technical debt (SATD) impairs scientific software (SSW), yet its prioritization, sentiment, persistence, and propagation remains underexplored. Understanding how SSW developers express, and address SATD is crucial for improving SSW maintenance, and tooling. This study investigates how SATD types and artifacts in SSW are prioritized, how sentiment relates to urgency, SATD removal and resolution rates, and the extent to which SATD propagates across artifacts. We analyzed nine SSW repositories using a SATD classification model and a semantic embedding-based prioritization heuristic. SATD was examined across multiple artifacts, with sentiment assessed via a fine-tuned transformer. Propagation was traced, priority scores compared to static analysis, and removal and resolution rates quantified. SATD in comments, commits, and pull requests receive higher priority than SATD in issues, with negative sentiment amplifying urgency. Resolution and removal rates lag behind open-source software (OSS) averages. Most SATD remains confined to the originating artifact, but longer propagation chains are rare and correlate with higher priority, highlighting persistent and high impact debt. Prioritization is influenced by artifact type and sentiment, while low removal and resolution rates signal persistent debt. Cross-artifact propagation marks high priority, unresolved SATD, providing empirical guidance for targeted monitoring, review prioritization, and tool supported maintenance in SSW.

Melin, Eric [Boise State University]↗
DOE OSTI2025

Numerical assessment of triply periodic minimal surfaces for direct air capture of carbon dioxide

Direct air capture (DAC) systems often consist of packing material wetted by a capture fluid that reacts with CO 2 in the airstream. The efficiency of the contactor is determined by a complex relationship of fluid dynamics, heat and mass transfer, contactor geometry, and chemical properties. The efficiency of the contactor must be balanced with other factors, primarily pressure drop through the system. Triply periodic minimal surfaces (TPMS) are a class of differential surfaces that have been explored in multiple engineering applications and have been shown to exhibit excellent performance when used in heat exchangers. Their tortuous path provides a high surface-to-volume ratio and favorable trade-off between contact area and pressure drop. In this work, a gyroid-type TPMS contactor was evaluated using computational fluid dynamics for a variety of geometric parameters to explore the potential benefit of TPMS shapes for DAC applications. A thin-film model was employed to model the flow and distribution of the capture solvent, allowing efficient simulations of TPMS structures at scale by eliminating the need for a computationally intensive interface capturing method. A liquid-gas mass transfer model was implemented in the commercial software STAR-CCM+ and used to predict the CO 2 capture efficiency and study the trade-off between capture performance and pressure drop through analysis of capture rates, mass transfer coefficients, and other relevant variables. TPMS contactors with a variety of geometric parameters and two capture solvent options were investigated to determine the effect of design choices on the operational performance of DAC systems. In conclusion, results showed that while contactor geometry is the dominant factor in efficiency and pressure drop, the physiochemical properties of the solvent are an important secondary influence on the contactor performance.

CFD↗
DOE OSTI2025

Data from a throughfall exclusion experiment: Fine root dynamics, morphology, chemistry, and AMF colonization across four lowland Panamanian forests

Fine roots regulate forest nutrient, carbon, and water cycling, yet their variation within and among tropical forests remains under-characterized. We quantified root productivity, disappearance, and stocks to 1 m using minirhizotron imaging, and we measured morphology, elemental composition [root carbon (C), root nitrogen (N), root phosphorus (P)], and arbuscular mycorrhizal fungi (AMF) colonization to 20 cm using ingrowth cores and sequential coring. Sampling took place in four distinct lowland Panamanian forests (32 plots; 8 per forest) from 2018 through 2022 under control and throughfall-exclusion (drought) treatments in the Panama Rainforest Changes with Experimental Drying (PARCHED) experiment.The dataset is presented as an Excel workbook with six tabs. The first tab is the data dictionary. Tab S1 contains ingrowth-core production and mortality, morphology and soil moisture. Tab S2 contains sequential-coring standing stocks with associated morphology and soil moisture. Tab S3 contains minirhizotron row data records to 1 m depth, including per-frame root length and diameter, normalized length metrics, and session timing. Tab S4 contains AMF colonization. Tab S5 contains fine-root chemistry at 0–10 cm, reporting %P, %C, %N, and C:N for samples collected via ingrowth cores and sequential-coring standing stocks. CSV mirrors for each tab are provided, and a KML file supplies coordinates for all 32 plots.Key variables span live and dead fine-root biomass (and coarse fractions where applicable), specific root length (SRL) and area (SRA), diameter, root tissue density (RTD), soil moisture, AMF colonization, root %N, %C, %P, and C:N, along with minirhizotron root length and diameter. Depth, season, treatment, and plot/site identifiers are included to support cross-tab integration and analysis from 0–100 cm (minirhizotron) and 0–20 cm (cores).Units are reported in-column and missing values are coded as NA. No special software is required to open or use the files (Excel, CSV, and KML compatible).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large-scale prediction of outer-membrane multiheme cytochromes uncovers hidden diversity of electroactive bacteria and underlying pathways

Multi-heme cytochromes (MHCs), together with accessory proteins like porins and periplasmic cytochromes, enable microbes to transport electrons between the cytoplasmic membrane and extracellular substrates (e.g., minerals, electrodes, other cells). Extracellular electron transfer (EET) has been described in multiple systems; yet, the broad phylogenetic and mechanistic diversity of these pathways is less clear. One commonality in EET-capable systems is the involvement of MHCs, in the form of porin-cytochrome complexes, pili-like cytochrome polymers, and lipid-anchored extracellular cytochromes. Here, we put forth MHCscan—a software tool for identifying MHCs and identifying potential EET capability. Using MHCscan, we scanned ~60,000 bacterial and 2,000 archaeal assemblies, and identify a diversity of MHCs, many of which represent enzymes with no known function, and many found within organisms not previously known to be electroactive. In total, our scan identified ~1,400 unique enzymes, each encoding more than 10 heme-binding motifs. In our analysis, we also find evidence for modularity and flexibility in MHC-dependent EET pathways, and suggest that MHCs may be far more common than previously recognized, with many facets yet to be discovered. We present MHCscan as a lightweight and user-friendly software tool that is freely available: https://github.com/Arkadiy-Garber/MHCscan.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO 2 F 2 ), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO 2 F 2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. Finally, during this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

wastewater_virus

This repo contains software used to clean and assemble high-throughput sequencing data containing viruses. The input is raw illumina sequencing reads and the output is a database of high-quality viral genomes. The specific application is to wastewater viral concentrates but it is not restricted to that sample type. The software is composed of Nextflow workflows and a set of custom Python and bash scripts that call publicly available bioinformatics tools to accomplish obvious tasks in data analysis in a high performance computing environment. For detailed information, please see the repo's README file.

Kantor, Rose [Lawrence Livermore National Laborato↗
DOE OSTI2025

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗
DOE OSTI2024

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Sierra/SD – Its2Sierra – User’s Manual – 5.28

Incrementally updated theory documents associated with new software release. The Integrated Tiger Series (ITS) generates a database containing energy deposition data. This data, when stored on an Exodus file, is not typically suitable for analysis within Sierra Mechanics for finite element analysis. The its2sierra tool maps data from the ITS database to the Sierra database. This document provides information on the usage of its2sierra.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

MARIE: A Python-Based Framework for Comprehensive Fuel Recycling Modeling

One of the most pressing challenges to the continued deployment of nuclear energy systems is in the ultimate management and disposition of discharged fuel assemblies. While reprocessing and recovery of valuable materials from UNF assemblies has been considered as part of an overall strategy for minimization of the volume of reactor-based wastes to be managed, the deployment of commercial-scale reprocessing facilities presents an enormous economic challenge. The MARIE software package has been developed as a means of confronting this challenge. Representing components of a generic fuel reprocessing operation as individual physical processes, MARIE is designed as a modular framework intended to allow for analysis and cost-optimization for a hypothetical reprocessing facility while realistically accounting for the physical characteristics of the used fuel source term, such as decay heat, activity, and radiation dose (informing corresponding shielding requirements). Capabilities supported by MARIE include head-end operations such as fuel shearing, voloxidation, and dissolution; generic solvent extraction operations informed by available open-literature data; a suite of unit operations intended to represent electrochemical processing of used fuel assemblies (i.e., oxide reduction, electrorefining, and electrowinning); and finally, accounting for both costs and physical features of discharged waste streams, which can be used to inform follow-on analyses such as the feasibility of deep-borehole disposal of HLW. This paper presents an overview of the MARIE software capabilities, including how individual unit operations are implemented to enable a larger-scale optimization of a hypothetical reprocessing operation on aspects such as cost and recovery of valuable materials.

Skutnik, Steve [ORNL] (ORCID:000000016441135X)↗
DOE OSTI2025

Oklo Sponsored Testing using PELICAN: System, Subchannel, and High-Fidelity Software Validation (Final CRADA Report)

Argonne National Laboratory (the Contractor), located in Lemont IL, and Oklo, Inc., (the Participant), headquartered in Santa Clara, CA, propose to enter into a Cooperative Research and Development Agreement (CRADA) to perform a gap analysis of thermal hydraulic data, perform prototypical fuel assembly pressure drop and cavitation model validation, generate the experimental data as well as the corresponding uncertainties for this matrix and, finally, develop the validation models with the Argonne system level code SAS4A/SASSYS-1, the Argonne subchannel analysis code DASSH, the Argonne high fidelity code Nek5000, and/or the Idaho National Laboratory code Pronghorn Subchannel. The work outlined below will significantly improve the experimental and validation database currently available for liquid metal fast reactors, thus making it a viable part of a comprehensive reactor design and licensing suite to be used by the participant.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

MCNPy

SAND2026-20425O MCNPy runs and analyzes simulations from MCNP, a software that models radiation transport of neutrons and gamma rays. MCNPy uses Python to start MCNP, retrieve event data files, and convert them into graph structures for detailed analysis. It offers visualization tools, including 2D views of particle histories, making complex simulation data easier to interpret for researchers and engineers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Nowack, Aaron [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2024

Hydrodynamic Test Requirements Process Improvements

Hydrodynamic testing at Los Alamos National Laboratory would benefit from a process improvement for the requirements process. Cameo was used as a digital solution for requirements management to allow Lead Engineers to track requirements more effectively. This was identified as a process improvement throughout this Capstone project. This report includes a project proposal, business case, literature review, methodology, project plan, data analysis, decision-making report, financial analysis report, discussion, and conclusion. Initially, this project focused on figuring out a solution for the hydrotest requirement process improvements. The scope narrowed to focus on the use of Cameo for requirement capture and management. During this Capstone, four tests had digital models produced for requirements management in Cameo. The initial model was the baseline, with core requirements used across the tests. Commonalities in tests were used and the core requirements allowed for process efficiencies. In the data analysis, it was seen that overall, the implementation of using Cameo for requirements resulted in a decreasing trend for both schedule and normalized cost. Tests have different complexity levels which is also a factor in how long the requirements process will take. Additional data is needed to continue analyzing process improvements. Through decisionmaking and financial analysis, the recommendation was to use Cameo for requirements process improvement. Multiple experts provided feedback for requirements that were then captured within models. Numerous tangible and intangible benefits were identified with this process improvement. For return on investment, the metric of success was schedule reduction, which was overall seen. Four tests were analyzed, so future analysis will be needed. There is also not a great financial risk because the main cost would be purchasing more licenses. Individuals must generate requirements whether using this software or not. Overall, training is needed to help improve the skillsets of Lead Engineers but is already being supported on a regular frequency. A desktop guide was started associated with explaining the process, however, it is a work in progress. The team plans on adding additional information in the digital models to help status when requirements are met using verification methods and artifacts. From working on this project an improved understanding of Cameo and requirements was the result. There are future opportunities to extend the usage for requirements management and progress will continue after this project.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Improving the User Interface of the DeepLynx Data Warehouse

DeepLynx is an open-source ontology-based data warehouse created by INL to support the creation and life cycle of digital engineering projects, with a particular emphasis on digital twins [1]. Digital twins are systems that represent physical assets and process in a real-time digital environment [1]. Most well-known commercial data warehouses use Graphical User Interfaces (GUIs) for users to interact with their systems [3]. Limited publications have addressed the design of these interfaces and understanding of their target users. The current users and development team acknowledge the need to improve the current UI, not just for aesthetics but to improve functionality and workflow of DeepLynx. Traditional data warehouse users are developers, data scientists and business analysts [2]. DeepLynx users have a vast range of experience using data warehouses, and diverse roles, including engineers, scientists and management positions. Because there is a broader audience of target users for DeepLynx than a typical data warehouse, it is essential that DeepLynx has a useable and intuitive user interface. To achieve this the team performed human-computer interaction methods, including a Heuristic Evaluation of current UI using Neilsen’s Usability Heuristic, create personas based on current users by designing a user survey, data analysis and develop of personas. Followed by a redesign of the UI following using Neilsen’s Usability Heuristic and Norman’s Principles of Interactive Design in industry standard software Figma. Lastly a Heuristic Evaluation of new UI design, using Neilsen’s Usability Heuristic and User testing of redesign UI and have a group of users complete a Thinking Aloud Test of the new UI. Preliminary results of the Heuristic Evaluation of current UI arise issue with Consistency and Standards, Visibility of System Status, Match System and Real World and Recognition Rather than Recall. These issues were addressed in the proposed redesign by applying Neilsen’s Usability Heuristic and Norman’s Principles of Interactive Design. Next steps include formalized list of lessons learned and design implications for future publications.

97 MATHEMATICS AND COMPUTING↗