Search NASA⌕ Search

SEARCH · Search NASA

Results for “Matlab data”

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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis

The nodal admittance matrix (NAM)-based approach is suitable for analyzing the small-signal stability of large-scale power electronics-based power systems (PEPSs) as it preserves the system structure by utilizing the admittance matrix. Previously, NAM-based area partition has been proposed, which divides the system into various subareas and interconnections for easier analysis of the low-dimension matrix compared to the entire system-based high-dimension matrix. However, no partition algorithm has been presented for the NAM-based area partition method. This paper focuses on implementing the spectral partitioning algorithm for partitioning large-scale PEPSs into a low-dimension matrix to reduce the computation complexity of the analysis. These spectral components facilitate data transformation into a new space, enabling the application of traditional clustering methods like k-means. To evaluate the performance of the partitioning method, the subareas and interconnections obtained from the spectral clustering algorithm are incorporated into the NAM-based area partition method for a large system with 140 buses. The computational times of the original method, where the NAM-based criterion is directly applied to the entire system, are compared with those of the NAM-based partition method in MATLAB. PSCAD simulations of the whole system and the obtained subareas are conducted to validate the effectiveness of the proposed algorithm.

Nupur, Nupur↗
DOE OSTI2016

SU-F-J-180: A Reference Data Set for Testing Two Dimension Registration Algorithms

Purpose: To create and characterize a reference data set for testing image registration algorithms that transform portal image (PI) to digitally reconstructed radiograph (DRR). Methods: Anterior-posterior (AP) and Lateral (LAT) projection and DRR image pairs from nine cases representing four different anatomical sites (head and neck, thoracic, abdominal, and pelvis) were selected for this study. Five experts will perform manual registration by placing landmarks points (LMPs) on the DRR and finding their corresponding points on the PI using computer assisted manual point selection tool (CAMPST), a custom-made MATLAB software tool developed in house. The landmark selection process will be repeated on both the PI and the DRR in order to characterize inter- and -intra observer variations associated with the point selection process. Inter and an intra observer variation in LMPs was done using Bland-Altman (B&A) analysis and one-way analysis of variance. We set our limit such that the absolute value of the mean difference between the readings should not exceed 3mm. Later on in this project we will test different two dimension (2D) image registration algorithms and quantify the uncertainty associated with their registration. Results: Using one-way analysis of variance (ANOVA) there was no variations within the readers. When Bland-Altman analysis was used the variation within the readers was acceptable. The variation was higher in the PI compared to the DRR.ConclusionThe variation seen for the PI is because although the PI has a much better spatial resolution the poor resolution on the DRR makes it difficult to locate the actual corresponding anatomical feature on the PI. We hope this becomes more evident when all the readers complete the point selection. The reason for quantifying inter- and -intra observer variation tells us to what degree of accuracy a manual registration can be done. Research supported by William Beaumont Hospital Research Start Up Fund.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Utah FORGE: Phase 3 InSAR Study Results

Ground movement is evaluated through analysis of Interferometric Synthetic Aperture Radar (InSAR) interferograms. Results indicate there has been no detectable ground movement at millimeter scale. The zipped file in this submission contains a report, maps, and results from the InSAR Phase 3 study done to determine ground crustal deformation, if any, in the Utah FORGE area. The data used to facilitate this study included synthetic aperture radar data acquired by the TerraSAR-X and TanDEM-X satellite missions operated by the German Space Agency (DLR). It is accompanied by a README.txt file which further describes each included dataset.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Computational Modeling of Micrometastatic Breast Cancer Radiation Dose Response

Purpose: Prophylactic cranial irradiation (PCI) involves giving radiation to the entire brain with the goals of reducing the incidence of brain metastasis and improving overall survival. Experimentally, we have demonstrated that PCI prevents brain metastases in a breast cancer mouse model. We developed a computational model to expand on and aid in the interpretation of our experimental results. Methods and Materials: MATLAB was used to develop a computational model of brain metastasis and PCI in mice. Model input parameters were optimized such that the model output would match the experimental number of metastases per mouse from the unirradiated group. An independent in vivo–limiting dilution experiment was performed to validate the model. The effect of whole brain irradiation at different measurement points after tumor cells were injected was evaluated in terms of the incidence, number of metastases, and tumor burden and was then compared with the corresponding experimental data. Results: In the optimized model, the correlation between the number of metastases per mouse and the experimental fits was >95. Our attempt to validate the model with a limiting dilution assay produced 99.9% correlation with respect to the incidence of metastases. The model accurately predicted the effect of whole-brain irradiation given 3 weeks after cell injection but substantially underestimated its effect when delivered 5 days after cell injection. The model further demonstrated that delaying whole-brain irradiation until the development of gross disease introduces a dose threshold that must be reached before a reduction in incidence can be realized. Conclusions: Our computational model of mouse brain metastasis and PCI correlated strongly with our experiments with unirradiated mice. The results further suggest that early treatment of subclinical disease is more effective than irradiating established disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-C-304-04: A Compact Modular Computational Platform for Automated On-Board Imager Quality Assurance

Purpose: Traditionally, the assessment of X-ray tube output and detector positioning accuracy of on-board imagers (OBI) has been performed manually and subjectively with rulers and dosimeters, and typically takes hours to complete. In this study, we have designed a compact modular computational platform to automatically analyze OBI images acquired with in-house designed phantoms as an efficient and robust surrogate. Methods: The platform was developed as an integrated and automated image analysis-based platform using MATLAB for easy modification and maintenance. Given a set of images acquired with the in-house designed phantoms, the X-ray output accuracy was examined via cross-validation of the uniqueness and integration minimization of important image quality assessment metrics, while machine geometric and positioning accuracy were validated by utilizing pattern-recognition based image analysis techniques. Results: The platform input was a set of images of an in-house designed phantom. The total processing time is about 1–2 minutes. Based on the data acquired from three Varian Truebeam machines over the course of 3 months, the designed test validation strategy achieved higher accuracy than traditional methods. The kVp output accuracy can be verified within +/−2 kVp, the exposure accuracy within 2%, and exposure linearity with a coefficient of variation (CV) of 0.1. Sub-millimeter position accuracy was achieved for the lateral and longitudinal positioning tests, while vertical positioning accuracy within +/−2 mm was achieved. Conclusion: This new platform delivers to the radiotherapy field an automated, efficient, and stable image analysis-based procedure, for the first time, acting as a surrogate for traditional tests for LINAC OBI systems. It has great potential to facilitate OBI quality assurance (QA) with the assistance of advanced image processing techniques. In addition, it provides flexible integration of additional tests for expediting other OBI quality assurance tests, such as 2D/3D image quality, making completely automated QA possible. Research Funding from Varian Medical Systems Inc. . Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

TEAMER: Numerical Modeling and Optimization of the iProTech Pitching Inertial Pump (PIP) Wave Energy Converter (WEC)

This project focused on developing an automated workflow to evaluate and optimize the iProTech Pitching Inertial Pump (PIP) wave energy converter (WEC) using open-source Python packages and the MATLAB/Simulink tool, WEC-Sim. The process involved parameterizing key design variables, running time-domain simulations, and performing sensitivity analyses to determine their impact on power output. The workflow, designed for the PIP device, is generalized and can be extended to optimize other WECs that can be simulated in WEC-Sim. This work establishes a foundation for future time-domain-based WEC design optimizations. Included in this submission are all figures from the final report and the model inputs required to generate them. This includes Python scripts with inputs that produce the meshes, boundary element method (BEM) models, hydrodynamic coefficients, and the WEC-Sim models used for time-domain analyses. Although data for every single run is not included to save space, all of it can be reproduced using the provided models. Detailed instructions for setting up the environment and running the codes are also included.

16 TIDAL AND WAVE POWER↗
DOE OSTI2011

Automatic Diabetic Macular Edema Detection in Fundus Images Using Publicly Available Datasets

Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publicly available datasets are employed to evaluate our algorithm. We are able to achieve diagnosis performance comparable to retina experts on the MESSIDOR (an independently labelled dataset with 1200 images) with cross-dataset testing. Our algorithm is robust to segmentation uncertainties, does not need ground truth at lesion level, and is very fast, generating a diagnosis on an average of 4.4 seconds per image on an 2.6 GHz platform with an unoptimised Matlab implementation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Pre-Commercial Demonstration of Direct Non-Iterative State Estimator (DNSE+)

The objective of this DOE co-funded project is to demonstrate functionality and performance of a production-grade Direct Non-iterative State Estimator (DNSE) through its integration with NYPA’s Energy Management System (EMS) and an enhanced Real Time Dynamics Monitoring System (RTDMS) synchrophasor platform from Electric Power Group (EPG). A production-grade DNSE aims to overcome a major obstacle to the operational use of synchrophasor data in Synchro-Phasor Management Systems (SPMS) by providing SPMS applications with a consistent and a complete synchrophasor data foundation in the same way that a traditional EMS State Estimator (SE) provides to EMS applications. Specifically, the DNSE uses synchrophasor measurements and Supervisory Control and Data Acquisition (SCADA) measurements, together with the complete power system model, to simultaneously obtain the complete state of the entire utility’s operating model at rates that are close to the synchrophasor data rates. The full system coverage property is what distinguishes the DNSE from the linear synchrophasor SEs (which cover only parts of the operating model that are visible through synchrophasor measurements), and DNSE differs from traditional EMS SE in that the solution is obtained without iterations, without initial values (hence the “direct” in the name), and at a much higher execution rate. This presentation provides an overview of the project objectives, a brief description of the main tasks including the development work to productize and optimize DNSE from its current MATLAB code base, RTDMS enhancement for interfacing with the DNSE, factory acceptance testing, field installation, testing and demonstration, as well as the current status of the project execution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

TH-C-BRD-01: Analytical Computation of Prompt Gamma Ray Emission and Detection for Proton Range Verification

Purpose: A prompt gamma (PG) slit camera prototype demonstrated that on-line range monitoring within 1–2 mm could be performed by comparing expected and measured PG detection profiles. Monte Carlo (MC) can simulate the expected PG profile but this would result in prohibitive computation time for a complete pencil beam treatment plan. We implemented a much faster method that is based on analytical processing of pre-computed MC data. Methods: The formation of the PG detection signal can be separated into: 1) production of PGs and 2) detection by the camera detectors after PG transport in geometry. For proton energies from 40 to 230 MeV, PG productions in depth were pre-computed by MC (PENH) for 12C, 14N, 16O, 31P and 40Ca. The PG production was then modeled analytically by adding the PG production for each element according to local proton energy and tissue composition.PG transport in the patient/camera geometries and the detector response were modeled by convolving the PG production profile with a transfer function. The latter is interpolated from a database of transfer functions fitted to pre-computed MC data (PENELOPE). The database was generated for a photon source in a cylindrical phantom with various radiuses and a camera placed at various positions.As a benchmark, the analytical model was compared to PENH for a water phantom, a phantom with different slabs (adipose, muscle, lung) and a thoracic CT. Results: Good agreement (within 5%) was observed between the analytical model and PENH for the PG production. Similar accuracy for detecting range shifts was also observed. Speed of around 250 ms per profile was achieved (single CPU) using a non-optimized MatLab implementation. Conclusion: We devised a fast analytical model for generating PG detection profiles. In the test cases considered in this study, similar accuracy than MC was achieved for detecting range shifts. This research is supported by IBA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Progress Report on Model Development for Aerosol Transport through Divergent Cracks Paths

This report summarizes the progress in developing a phenomenological model of aerosol transport, deposition, and plugging through microchannels. The purpose of this effort is to introduce to a user community—involving researchers, regulators, and industry—a generic, reliable numerical model for the prediction of aerosol transport while accounting for potential deposition and plugging of the leak paths to model spent nuclear fuel (SNF) release from postulated Stress Corrosion Cracks in canisters under storage or transportation. Current work focuses on expanding the model to predict aerosol (and gas) flow through complex microchannel (nozzle) geometries in addition to the rectangular and cylindrical geometries, as we approach more realistic Stress Corrosion Crack conditions. In this regard, a divergent nozzle geometry, used at Sandia National Laboratories (SNL) for testing aerosol release and retention (Durbin et al. 2021), was added to the model. The model was then validated with blowdown data for the particular microchannel, from experiments conducted at SNL. The report also presents preliminary non-benchmarked aerosol penetration fraction and mass flow rate for a monodisperse 10-micron (AED) particle concentration of 1.7e-08 kg/m 3 being released through the divergent microchannel geometry from the SNL’s aerosol experimental tank setup.Future work will involve validating the aerosol model and updating the model’s Graphical User Interface (GUI) to include the divergent nozzle geometry. This is expected to help stakeholders perform quick and easy first principles calculations without needing to understand the underlying MATLAB script.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Methods to measure contact angles in scCO 2 -brine-sandstone systems

Numerous methods are used to measure contact angles ( θ ) in multiphase systems. The wettability and θ are primary controls on CO 2 residual trapping during Geologic Carbon Storage (GCS) and determining these values within rock pores is paramount to increasing storage efficiency. One traditional experimental approach is the sessile drop method which involves θ measurements on a single image of droplets. More recent developments utilize X-ray micro-computed tomography (CT) scans which provide the resolutions necessary to image in situ θ of fluids at representative conditions; however, experimental micro-CT data is limited and varied. To further examine θ distributions in supercritical-CO 2 -brine-sandstone systems, a combination of manual and automated θ measurement methods were utilized to measure θ using both sessile drop and micro-CT images of two sandstone cores. Here, the purpose of this work was threefold: (1) compare two current and two new θ measuring methods using micro-CT images of scCO 2 -brine-sandstone systems; (2) determine how traditional experimental method (sessile drop) θ results compare to in situ θ results (micro-CT); and (3) determine if the Matlab Contact Angle Algorithm (MCAA) from Klise et al. (2016) can be used to measure θ scCO 2 -brine-sandstone systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Detection and correction for EPID and gantry sag during arc delivery using cine EPID imaging

Purpose: Electronic portal imaging devices (EPIDs) have been studied and used for pretreatment and in-vivo dosimetry applications for many years. The application of EPIDs for dosimetry in arc treatments requires accurate characterization of the mechanical sag of the EPID and gantry during rotation. Several studies have investigated the effects of gravity on the sag of these systems but each have limitations. In this study, an easy experiment setup and accurate algorithm have been introduced to characterize and correct for the effect of EPID and gantry sag during arc delivery. Methods: Three metallic ball bearings were used as markers in the beam: two of them fixed to the gantry head and the third positioned at the isocenter. EPID images were acquired during a 360 deg. gantry rotation in cine imaging mode. The markers were tracked in EPID images and a robust in-house developed MATLAB code was used to analyse the images and find the EPID sag in three directions as well as the EPID + gantry sag by comparison to the reference gantry zero image. The algorithm results were then tested against independent methods. The method was applied to compare the effect in clockwise and counter clockwise gantry rotations and different source-to-detector distances (SDDs). The results were monitored for one linear accelerator over a course of 15 months and six other linear-accelerators from two treatment centers were also investigated using this method. The generalized shift patterns were derived from the data and used in an image registration algorithm to correct for the effect of the mechanical sag in the system. The Gamma evaluation (3%, 3 mm) technique was used to investigate the improvement in alignment of cine EPID images of a fixed field, by comparing both individual images and the sum of images in a series with the reference gantry zero image. Results: The mechanical sag during gantry rotation was dependent on the gantry angle and was larger in the in-plane direction, although the patterns were not identical for various linear-accelerators. The reproducibility of measurements was within 0.2 mm over a period of 15 months. The direction of gantry rotation and SDD did not affect the results by more than 0.3 mm. Results of independent tests agreed with the algorithm within the accuracy of the measurement tools. When comparing summed images, the percentage of points with Gamma index <1 increased from 85.4% to 94.1% after correcting for the EPID sag, and to 99.3% after correction for gantry + EPID sag. Conclusions: The measurement method and algorithms introduced in this study use cine-images, are highly accurate, simple, fast, and reproducible. It tests all gantry angles and provides a suitable automatic analysis and correction tool to improve EPID dosimetry and perform comprehensive linac QA for arc treatments.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

SU-E-J-268: Change of CT Number During the Course of Chemoradiation Therapy for Pancreatic Cancer

Purpose: It has been observed radiation can induce changes in CT number (CTN) inside tumor during the course of radiation therapy (RT) for several tumor sites including lung and head and neck, suggesting that the CTN change may be potentially used to assess RT response. In this study, we investigate the CTN changes inside tumor during the course of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily diagnostic-quality CT data acquired during IGRT for 17 pancreatic head cancer patients using an in-room CT (CTVision, Siemens) were analyzed. All patients were treated with a radiation dose of 50.4 in 1.8 Gy per fraction. On each daily CT set, The contour of the pancreatic head, included in the treatment target, was generated by populating the pancreatic head contour from the planning CT or MRI using an auto-segmentation tool based on deformable registration (ABAS, Elekta) with manual editing if necessary. The CTN at each voxel in the pancreatic head contour was extracted and the 3D distribution of the CTNs was processed using MATLAB. The mean value of CTN distribution was used to quantify the daily CTN change in the pancreatic head. Results: Reduction of CTN in pancreatic head was observed during the CRT delivery in 14 out the 17 (82%) patients studied. Although the average reduction is only 3.5 Houncefield Unit (HU), this change is significant (p<0.01). Among them, there are 7 patients who had a CTN drop larger than 5 HU, ranging from 6.0 to 11.8 HU. In contrast to this trend, CTN was increased in 3 patients. Conclusion: Measurable changes in the CT number in tumor target were observed during the course of chemoradiation therapy for the pancreas cancer patients, indicating this radiation-induced CTN change may be used to assess treatment response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Gravitation and Mesh Adaption

The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields

Pearl, Jason↗
DOE OSTI2022

Large-scale parametric modeling of spent nuclear fuel dynamics in the 30 cm package drop scenario

Packages used to transport spent nuclear fuel (SNF) are required by the U.S. Code of Federal Regulations 10 CFR 71.71 to demonstrate satisfactory performance during a drop scenario. While the CFR is meant to ensure safe package function, it does not evaluate survival of the SNF within. The U.S. Department of Energy Spent Fuel and Waste Science and Technology program is working on closing the knowledge gap related to the response of SNF to external mechanical loads, including the hypothetical 30 cm package drop scenario in the CFR. In support of this effort, LS-DYNA finite element simulations were developed by Pacific Northwest National Laboratory (PNNL) to model generic drop scenarios at both the package and fuel assembly level. The models were validated against one-third scale package and full scale fuel assembly drop test data and were exercised to predict fuel cladding strains in a narrow range of model configurations. This work describes a large-scale parametric study conducted by PNNL using the previously developed and validated PWR finite element model, with the addition of a new generic BWR assembly model. The motivation for the parametric study was to characterize the broad range of SNF responses in the 30 cm package drop scenario. This was accomplished by varying the drop orientation, fuel assembly type (17x17 PWR and 10x10 BWR), burnup, cladding temperature, spacer grid buckling load, package mass, impact limiter stiffness, and mechanical gap conditions within the basket. A MATLAB framework was developed to automate LS-DYNA model generation and execution on PNNL institutional computing resources. In total, over 2000 simulations were performed. For each simulation, the SNF response was quantified in terms of permanent grid deformation, fuel rod contact pressure, and strains within the fuel rods, guide tubes, and water rods. The results provide valuable insight into the range of responses that could be reasonably expected from SNF in the hypothetical drop scenario, as well as the sensitivity to each input parameter. The results of this parametric study are a key component of the testing and modeling strategy the Spent Fuel and Waste Science and Technology program is using to close the external loads knowledge gap.

Kadooka, Kevin↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗
DOE OSTI2020

Wave Tank Testing Report for Controls Validation of a Heaving Point Absorber

The core objectives of this project is to improve the power capture of three different wave energy conversion (WEC) devices by more than 50% using an advanced control system and validate the attained improvements using wave tank and full scale testing. In parallel, we will bring along the development of a wave prediction system that is required to enable effective control and test it at full scale. The purposes of this report are to: 1. Plan and document the 1/25th scale device testing at the wave-tank facility; 2. Document the test article, setup and methodology, sensor and instrumentation, mooring, electronics, wiring, and data flow and quality assurance; 3. Communicate the testing results between the associated members; 4. Facilitate reviews that will help to ensure all aspects (risk, safety, testing procedures, etc.); 5. Provide a systematic guide to setting up, executing and decommissioning the experiment.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Internship Work Report

I worked on two projects during my summer internship at Sandia. My official title was “Intern - Mission Tech Electrical Eng./Computer Eng.- R&D Undergraduate Summer.” I worked at the central location, which is Albuquerque, New Mexico. The department you are placed in at Sandia doesn’t always correspond to the people you will be working with. For example, I only directly worked with one person from my department this summer. On one of my projects, I worked with a diverse team of engineers from many different departments. On my other project, I mainly worked with two departments, as the project had two distinct parts. As mentioned earlier, I worked on two projects during my summer at Sandia. The first project focused on a lightweight embedded controller in an advanced FPGA System-on-Chip for radar signal processing applications. The term “controller” refers to a hardware device that directs the flow of data between two entities. An FPGA is a reprogrammable integrated circuit (as opposed to an integrated circuit with one purpose). An FPGA was used on this project so in order to protype various ideas for our System-on-Chip. My role on the project was to implement designs on the fabric of the FPGA and design a state machine (written in C) for the processor. My second project was also heavily involved with embedded systems but had a different application. It focused on using a Newton-Raphson control algorithm to stabilize an inverted pendulum using a novel microcontroller. The pendulum dynamics were derived, and it was successfully simulated in MATLAB. I worked on integrating the microcontroller with the inverted pendulum machinery, and converting the Newton-Raphson control algorithm from MATLAB into C. The inverted pendulum was successfully stabilized using a simple PID controller and industry-standard microcontroller. The project is still ongoing, and the team is gearing up for more tests using the novel Newton-Raphson control algorithm and novel microcontroller

42 ENGINEERING↗