Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “software: data analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

NWGraph: A Library of Generic Graph Algorithms and Data Structures in C++20

The C++ Standard Library is a valuable collection of generic algorithms and data structures that improves the usability and reliability of C++ software. Graph algorithms and data structures are notably absent from the standard library, and previous attempts to fill this gap have not gained widespread adoption. In this paper we show that the richness of graph algorithms and data structures can in fact be captured by straightforward composition of existing C++ mechanisms. Generic programming is algorithm-oriented. Accordingly, we apply a systematic approach to analyzing a broad set of graph algorithms, “lift” unnecessary constraints from them, and organize the resulting set of minimal common type requirements, i.e., concepts, for defining their interfaces. By using the newly available ranges and concepts in C++20, the type requirements for generic graph algorithms can be succinctly expressed. The generic algorithms and data structures resulting from our analysis are realized in NWGraph, in a modern, composable, and extensible C++ library.

graphs and networks, programming language, C++20↗
DOE OSTI2021

Critical analysis of velocimetry methods for particulate flows from synthetic data

Particle tracking methods that extract high-fidelity particle velocity data from high speed video of particle laden flows is a common experimental technique applied to chemical processes. These measurements are used to better understand the motion of particles and fluids in complex systems and create data against which computational models are validated. However, the methods, codes, and experimental setups all have limitations. It is imperative that practitioners verify the methods and their implementation as well as understand the limitations of experimental setups. This work focuses on quantifying the visible depth of field in a high particle concentration fluidized bed. Following a precedent set by the particle imaging velocimetry community, a particle velocity field is manufactured using a computational fluid dynamics and discrete element method simulation. Photo realistic high-speed videos are rendered based on the simulated data using the three-dimensional creation software Blender. Particle velocities are extracted from the synthetic high-speed videos using three variants of Particle Tracking Velocimetry and Optical Flow Velocimetry methodologies. Here, the tracked results are then compared to the known solution, quantifying the error associated with the assumed visible depth. The results indicate that at depth of one particle diameter, all three particle tracking codes give accurate measurements, largely within 5%. However, the error increases when the full bed video measurements are compared to the known solution at one particle diameter, i.e., mimicking a validation study. Finally, for some statistics the constant depth assumption only increases the error slightly, for others significantly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Replacing photomultiplier tubes with silicon photomultipliers for nuclear safeguards applications

Photomultiplier tubes (PMTs) have been used for decades as the default light detection technology for scintillator-based radiation monitors. PMTs come with a handful of disadvantages, however, including large volume usage, fragility, high-voltage requirements, and susceptibility to magnetic fields. Arrays of silicon photomultipliers (SiPMs) are a possible alternative to PMTs providing similar performance while offering improvements in the areas listed. We focus on straightforward “drop-in replacement” evaluations by imposing a single channel output of the SiPM signal and a backend electronics data acquisition and analysis routine identical to that used for PMTs. In the realm of nuclear safeguards, the primary performance metric for gamma spectroscopy is detector resolution, and for neutron detection it is pulse shape discrimination (PSD) to separate neutron and gamma signals. In this work we present the results of replacing a PMT with a 2” x 2” SiPM array mounted, in turn, to the same 2” x 2” cylindrical sodium iodide (NaI) crystal. The ultimate comparison for this gamma spectrometry is confirmation of uranium enrichment standards, ranging from depleted uranium to 93% highly enriched uranium (HEU), by analyzing the resulting spectra with both a simple integral scaling in key energy regions of the spectrum, as well as with the NaIGEM software package. In addition to the gamma spectroscopy work, we will present the latest results on comparing the PSD capabilities of a 4” x 4” SiPM array to a 5” PMT. As with the gamma spectroscopy evaluations, the light detectors are mounted in turn to the same liter-scale organic scintillators. This neutron-focused work includes evaluation of prototype SiPM readout boards with a single output signal summed over 256 individual SiPM pixels, and evident tradeoffs between PSD capability and fast response.

42 ENGINEERING↗
DOE OSTI2021

Understanding HPC Benchmark Performance on Intel Broadwell and Cascade Lake Processors

Hardware platforms in high performance computing are constantly getting more complex to handle even when considering multicore CPUs alone. Numerous features and configuration options in the hardware and the software environment that are relevant for performance are not even known to most application users or developers. Microbenchmarks, i.e., simple codes that fathom a particular aspect of the hardware, can help to shed light on such issues, but only if they are well understood and if the results can be reconciled with known facts or performance models. The insight gained from microbenchmarks may then be applied to real applications for performance analysis or optimization. In this paper we investigate two modern Intel x86 server CPU architectures in depth: Broadwell EP and Cascade Lake SP. We highlight relevant hardware configuration settings that can have a decisive impact on code performance and show how to properly measure on-chip and off-chip data transfer bandwidths. The new victim L3 cache of Cascade Lake and its advanced replacement policy receive due attention. Finally we use DGEMM, sparse matrix-vector multiplication, and the HPCG benchmark to make a connection to relevant application scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

2019 Computing Sciences Strategic Plan

Computing has transformed nearly every aspect of scientific inquiry — across disciplines and across scales — from the behavior of subatomic particles to the formation of structures in the early universe, from the assembly of the human genome to the evolution of earth systems. Over the past two decades, computing has become an integral part of how Berkeley Lab is “Bringing Science Solutions to the World.” Advances in computing and mathematics have been key, with new mathematical models of complex physical phenomena, new methods for analyzing complex data, new algorithms for accuracy and scaling and sophisticated software systems that encapsulate these techniques into open, reusable tools. The performance of NERSC computers and the ESnet network have grown by several orders of magnitude, along with our understanding of how to map scientific computations and workflows onto these systems. From research to facility operations, the passion, talent and dedication of the Computing Sciences Area staff has been the cornerstone of our success. The plan outlined in this document describes the next step in a journey to expand the influence and impact of our efforts, building an increasingly connected global enterprise for science that places more powerful instruments in the hands of scientists, along with more powerful methods and tools for modeling, analysis and prediction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Replacing photomultiplier tubes with silicon photomultipliers for nuclear safeguards applications

Photomultiplier tubes (PMTs) have been used for decades as the default light detection technology for scintillator-based radiation monitors. PMTs come with a handful of disadvantages, however, including large volume usage, fragility, high-voltage requirements, and susceptibility to magnetic fields. Arrays of silicon photomultipliers (SiPMs) are a possible alternative to PMTs providing similar performance while offering improvements in the areas listed. We focus on straightforward “drop-in replacement” evaluations by imposing a single channel output of the SiPM signal and a backend electronics data acquisition and analysis routine identical to that used for PMTs. In the realm of nuclear safeguards, the primary performance metric for gamma spectroscopy is detector resolution, and for neutron detection it is pulse shape discrimination (PSD) to separate neutron and gamma signals. In this work we present the results of replacing a PMT with a 2” x 2” SiPM array mounted, in turn, to the same 2” x 2” cylindrical sodium iodide (NaI) crystal. The ultimate comparison for this gamma spectrometry is confirmation of uranium enrichment standards, ranging from depleted uranium to 93% highly enriched uranium (HEU), by analyzing the resulting spectra with both a simple integral scaling in key energy regions of the spectrum, as well as with the NaIGEM software package. In addition to the gamma spectroscopy work, we will present the latest results on comparing the PSD capabilities of a 4” x 4” SiPM array to a 5” PMT. As with the gamma spectroscopy evaluations, the light detectors are mounted in turn to the same liter-scale organic scintillators. This neutron-focused work includes evaluation of prototype SiPM readout boards with a single output signal summed over 256 individual SiPM pixels, and evident tradeoffs between PSD capability and fast response.

Engineering - Instrumentation related to nuclear s↗
DOE OSTI2021

Digital Infrastructure Migration Framework Report

This document presents a full-scope Digital Infrastructure implementation and associated lifecycle support recommendations that enable a plant life of 80+ years. Specific technologies and software applications are researched, developed, selected, implemented, and then integrated by utilities to enhance safety, reliability, and economic performance such that the result provides much more than the sum of its parts. Specific selection of these technologies is driven by business case analyses which are utility, station, and unit specific.

42 ENGINEERING↗
DOE OSTI2020

LOGOS

LOGOS is a software package which contains a set of discrete optimization models that can be employed for capital budgeting optimization problems. More specifically, provided a set of items (characterized by cost and reward values) and constraints, these models select the best combination of items which maximizes overall reward and satisfies the provided constraints. The developed models are based on different versions of the knapsack optimization algorithms. Two main classes of optimization models have been initially developed: deterministic and stochastic. Stochastic optimization models evolve deterministic models by explicitly considering data uncertainties (associated to constraints or item cost and reward). These models can be employed as stand-alone models or interfaced with the INL developed RAVEN code to propagate data uncertainties and analyze the generated data (i.e., sensitivity analysis).

Wang, Congjian↗
DOE OSTI2024

Schema Elements for Granta Annual Report: FY2024

Granta: Materials Intelligence (Granta: MI) is a commercial database software distributed by Ansys, Inc. that is utilized by the Nuclear Security Enterprise (NSE) to organize and store relevant materials data. Lack of standard and well-documented database schema is the primary obstacle to an NSE materials data management solution, so the objective of this project is to create and document such a schema. In FY21, an approach for designing, documenting, and managing a standard database schema was described based on the creation of schema elements (collections of attributes used to describe particular aspects of the data) to be used as building blocks for creating various database tables without duplication. In FY22, these methods were applied through a multi-site collaboration to create and document the schema elements necessary to build a thermogravimetric analysis (TGA) testing table. In FY23 the schema was expanded to include elements for a differential scanning calorimetry (DSC) table, along with schema for supporting metadata tables including Instruments, Projects, Documents, and Testing Series. In FY24 the following progress was made, again through multi-site collaboration: • The existing schema elements were modified to accommodate thermomechanical analysis (TMA) data, and a table, Test Data: TMA, was created for managing TMA data. • The elements necessary for the following additive manufacturing (AM) data tables (directed at data specific to selective laser sintering AM technology) were created: • AM Builds • AM Processes • AM Part Designs • Built AM Parts • AM Feedstock Materials • AM Feedstock Material Batches • The elements necessary for creating a Calibrated Material Models table were created, and the Calibrated Material Models table was created. In FY25 the existing schema will be deployed on the production enterprise Granta instance on the enterprise secure network. Schema elements will be appended, and new elements created as necessary, to allow the creation of tables specifically to support materials testing, AM process development, and design and analysis for modernization programs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Computational analysis of the tryptophan cation radical energetics in peroxidase Compound $\mathrm{I}$

Three well-characterized heme peroxidases (cytochrome c peroxidase = CCP, ascorbate peroxidase = APX, and Leishmania major peroxidase = LMP) all have a Trp residue tucked under the heme stacked against the proximal His heme ligand. The reaction of peroxidases with H 2 O 2 to give Compound I results in the oxidation of this Trp to a cationic radical in CCP and LMP but not in APX. Considerable experimental data indicate that the local electrostatic environment controls whether this Trp or the porphyrin is oxidized in Compound I. Attempts have been made to place the differences between these peroxidases on a quantitative basis using computational methods. These efforts have been somewhat limited by the approximations required owing to the computational cost of using fully solvated atomistic models with well-developed forcefields. This now has changed with available GPU computing power and the associated development of software. Here we employ thermodynamic integration and multistate Bennett acceptance ratio methods to help fine-tune our understanding on the energetic differences in Trp radical stabilization in all three peroxidases. These results indicate that the local solvent structure near the redox active Trp plays a significant role in stabilization of the cationic Trp radical.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Verification and validation of the Alternative Nonlinear Two-phase Subchannel (ANTS) code

The Alternative Nonlinear Two-phase Subchannel solver (ANTS) code was written to provide a fast-running, steady-state, pin-resolved modeling and simulation tool for analysis of common boiling water reactor (BWR) geometry and common operating conditions. ANTS has been integrated into the Virtual Environment for Reactor Application (VERA) core simulator software, where it can be used to provide a thermal/hydraulic (T/H) subchannel solution that is then used to provide neutronic feedback as well as perform the fuel depletion and temperature solution. Herein, this paper presents the rigorous analysis performed on the ANTS code, which includes both code and solution verification testing, benchmarking with the existing two-phase subchannel capability in VERA, CTF, and validation testing using popular two-phase experiments such as PWR Sub-channel and Bundle Tests (PSBT), BWR Full-size Fine-mesh Bundle Tests (BFBT), Risø, and FRIGG. This assessment was used to qualify ANTS for its intended applications before its use for core-scale, multiphysics BWR simulations. In general, it was found that agreement with experimental data was good; errors were within the range of experimental data uncertainty. Furthermore, code and solution verification confirmed that the governing equations and the most important closure terms were correctly implemented and behaving as expected.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Exploring Future Storage Options for ATLAS at the BNL/SDCC facility

The ATLAS experiment is expected to deliver an unprecedented amount of scientific data in the High Luminosity(HL-LHC) era. As the demand for disk storage capacity in ATLAS continues to rise steadily, the BNL Scientific Data and Computing Center (SDCC) faces challenges in terms of cost implications for maintaining multiple disk copies and adapting to the coming ATLAS storage requirements. To address these challenges, the SDCC Storage team has undertaken a thorough analysis of the ATLAS experiment's requirements, matching them to suitable storage options and strategies, and has explored alternatives to enhance or replace the current storage solution. This paper aims to present the main challenges encountered while supporting big data experiments such as ATLAS. We describe the experiment's specific requirements and priorities, particularly focusing on the critical storage system characteristics of the high-luminosity run and how the key storage components provided by the Storage team work together: the dCache disk storage system; its archival back-end, HPSS; and its OS-level backend Storage. Specifically, we investigate a novel approach to integrate Lustre and XRootD. In this setup, Lustre serves as backend storage and XRootD acts as an access layer frontend, supporting various grid access protocols. Additionally, we also describe the validation and commissioning tests, including the performance comparison between dCache and XRootd. Furthermore, we provide a performance and cost analysis comparing OpenZFS and LINUX MD RAID, evaluate different storage software stacks, and showcase stress tests conducted to validate Third Party Copy (TPC) functionality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Lighting System Control Data to Improve Design and Operation: Tunable Lighting System Data from NICU Patient Rooms

The advancement of LED and controls technology, computing capacity, and software provides new opportunities for researchers and designers to work together to further optimize spaces for occupant benefit. Here, lighting system control data from five neonatal intensive care unit patient rooms was collected over a 25-week monitoring period and analyzed to better understand occupant response to a tunable lighting system with automatic transitions throughout the day. Lighting systems are very rarely refined after installation based on actual use. Objective data detailing how the lighting system is used by the actual occupants highlights the opportunities for optimization after installation and provides insight for improving the next design. As use of the data becomes more commonplace, it can be leveraged for design recommendations. The collection of the data required no additional cost beyond the time for examining the data. The analysis revealed several clear opportunities for improvement, including adjustments to the default control setting at night, re-labeling of the control stations, and adjustments to the nighttime fade rate. The patient room occupants were active users of the different zones, dimming options, and manual overrides made available by the lighting system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Luke↗
DOE OSTI2022

Toward the Detection of Polyglot Files

Standardized file types play a key role in the development and use of computer software. However, it is possible to confound standardized file type processing by creating a file that is valid in multiple file types. The resulting polyglot (many languages) file can confuse file type identification, allowing elements of the file to evade analysis. This is especially problematic for malware detection systems that rely on file type identification for feature extraction. Although work has been done to identify file types using more comprehensive methods than file signatures, accurate identification of polyglot files remains an open problem. Since malware detection systems routinely perform file type-specific feature extraction, polyglot files need to be filtered out prior to ingestion by these systems. Otherwise, malicious content could pass through undetected. To address the problem of polyglot detection we assembled a data set using the mitra tool. We then evaluated the performance of the most commonly used file identification tools, including file, polydet, binwalk, and TrID. Our analysis demonstrates that existing file type detection tools fail to provide reliable polyglot detection. We then evaluated the ability of a range of machine and deep learning models to detect polyglot files. The most performant models were MalConv2 and Catboost, which demonstrated the highest recall on our data set with 95.16% and 95.45%, respectively. These models outperformed existing methods and could be incorporated into a malware detector’s file processing pipeline to filter out potentially malicious polyglots before file type-dependent feature extraction takes place.

Koch, Lucas↗
DOE OSTI2025

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗
DOE OSTI2024

Simulations, Modeling and Data Analysis of Parity Violating Electron Scattering Experiments

In the Standard Model (SM) of nuclear and particle physics, parity violation is incorporated through the representation of the weak interaction as a chiral gauge interaction. Only the left-handed components of particles and right-handed components of antiparticles participate in weak interactions in the Standard Model. This implies that parity is asymmetric for the weak interaction. Parity violating electron scattering (PVES) experiments are designed to probe the physics parameters related to the SM, with the possibility to discover physics beyond the SM (BSM) by measuring the parity violating asymmetry ¿¿¿ of longitudinally polarized electrons scattered off unpolarized targets with high precision. This dissertation will be focused on two PVES experiments, the next 208Pb Lead Radius Experiment (PREX-II), and the Measurement of a Lepton-Lepton Electroweak Reaction (MOLLER) experiment, as well as in some small sections, the Calcium Radius Experiment (CREX) and P2 experiment which are also PVES experiments). PREX-II and CREX experiments, performed in Hall A at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), measured ¿¿¿ in the elastic scattering of longitudinally polarized electrons from 208Pb and 48Ca targets to provide a precise model independent determination of the neutron skin thickness of 208Pb and 48Ca nuclei, respectively. The MOLLER experiment, proposed to start in 2027 and also to be performed in Hall A at Jefferson Lab, is to measure ¿¿¿ of longitudinally polarized electrons scattered off unpolarized electrons (Møller scattering) to determine the weak charge of electrons ¿¿¿ and the weak mixing angle ¿¿ with high precision. As for the P2 experiment, which will be performed at the upcoming MESA accelerator in Mainz Germany, it is to measure the weak charge of proton ¿¿¿ using ¿¿¿ in the elastic electron-proton scattering of polarized electrons off unpolarized protons. The final results from the PREX-II experiment are presented as ¿¿¿=550±16 (¿¿¿¿)±8 (¿¿¿¿) parts-per-billion (ppb). Combining the PREX-I and PREX-II results, the neutron skin thickness from PREX experiments is determined as ¿¿-¿¿=0.283±0.071 ¿¿ in 208Pb. This thesis lists the software and computational contribution of the author to these PVES experiments, including writing scripts and software to help with the PREX-II/CREX experiments, analyzing data to provide useful information and systematic uncertainty for the PREX-II experiment, modeling and simulations for the MOLLER, and providing an alternative design of an electronic equipment for the P2 experiment.

Chen, Yufan↗