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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.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Association of AK4 Protein From Stem Cell–Derived Neurons With Cognitive Reserve

Background and Objectives: Identifying protein targets that provide cognitive reserve is a strategy to prevent and treat Alzheimer disease and Alzheimer disease related dementias (AD/ADRD). Previous studies using bulk human brain tissue reported 12 proteins associated with cognitive reserve. This study examined whether the same proteins from induced neurons (iNs) are associated with cognitive reserve of their human donors. Methods: Here, induced pluripotent stem cell (iPSC) lines were generated from cryopreserved peripheral blood mononuclear cells of older adults who were autopsied as part of the Religious Orders Study or Rush Memory and Aging Project. Neurons were induced from iPSCs using a standard neurogenin2 protocol. Tandem mass tag proteomics analyses were conducted on iNs day 21. Cognitive reserve of their human donors was measured as person-specific slopes of cognitive change not accounted for by common neuropathologies. Results: The 53 human donors died at a mean age of 91 years, all were non-Latino White, and 36 (67.9%) were female. Eighteen were diagnosed with Alzheimer dementia proximate to death, and 34 had pathologic AD diagnosis at autopsy. Approximately 60% of the donors had above-average cognitive reserve such that their cognition declined slower than an average person with comparable burdens of neuropathologies. Eight of the 12 candidate proteins were quantified in iNs proteomics analyses. Higher adenylate kinase 4 (AK4) expression in iNs was associated with lower cognitive reserve, consistent with the previous report for brain AK4 expression. Discussion: By replicating cortical protein associations with cognitive reserve in human iNs, these data provide a valuable molecular readout for studying complex clinical phenotypes such as cognitive reserve in a dish.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software (Extended Analysis)

Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP) tensor decomposition model when the tensor has sparse structure and the tensor elements are nonnegative count data. SparTen is a high-performance C++ library which computes a low-rank decomposition using different solvers: a first-order quasi-Newton or a second-order damped Newton method, along with the appropriate choice of runtime parameters. Since default parameters in SparTen are tuned to experimental results in prior published work on a single real-world dataset conducted using MATLAB implementations of these methods, it remains unclear if the parameter defaults in SparTen are appropriate for general tensor data. Furthermore, it is unknown how sensitive algorithm convergence is to changes in the input parameter values. This report addresses these unresolved issues with large-scale experimentation on three benchmark tensor data sets. Experiments were conducted on several different CPU architectures and replicated with many initial states to establish generalized profiles of algorithm convergence behavior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Identifying a novel pathway for extracellular electron uptake in Methanosarcina barkeri using shotgun

The overarching goal of this project was to identify the genetic and/or enzymatic basis for extracellular electron uptake in Methanosarcina barkeri—an organism we previously characterized to be capable of this process using poised potential electrodes and a range of electrochemical techniques. In our first aim, we will utilized proteomic techniques that labels extracellular proteins with free amine groups with biotin and perform a selective purification of these proteins from the rest of the proteome. These were identified using mass spectrometry, providing us insight into the identity of the cell surface proteins, including redox active proteins present during extracellular electron uptake. We will also used an isobaric tagging technique (iTRAQ labeling) of proteomes from different experiment conditions to look at differential proteins expression and better understand the total pathway involved in extracellular electron uptake coupled to methanogenesis. In our final aim, we will investigated the electrochemical nature of electron uptake in co-cultures, compared to our pure culture data sets. We predict the process of electron uptake from electrodes replicates what goes on in nature when these organisms for co-cultures with electrogenic microbes such as Geobacter, and to test this hypothesis we have begun to probe co-cultures electrochemically during direct interspecies electron transfer. Our final aim took much longer than expected due to challenges replicating co-cultures between Geobacter metallireducens and Methanosarcina barkeri. We found the major problem with this work was the inability of the M. barkeri strain we used (and we tried strains from three different labs) to successfully grow on acetate in the absence of hydrogen. As such, we began to use the strain Methanosarcina acetivorans—another close relative that specializes on acetate growth. We are currently in the process of comparing electrochemical observations of this microorganism between pure and co-culture experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Corn Stover Removal Responses on Soil Test P and K Levels in Coastal Plain Ultisols

Corn (Zea mays L.) stover is used as a biofuel feedstock in the U.S. Selection of stover harvest rates for soils is problematic, however, because excessive stover removal may have consequences on plant available P and K concentrations. Our objective was to quantify stover harvest impacts on topsoil P and K contents in the southeastern U.S. Coastal Plain Ultisols. Five stover harvest rates (0, 25, 50, 75 and 100% by wt) were removed for five years from replicated plots. Grain and stover mass with P and K concentration data were used to calculate nutrient removal. Mehlich 1 (M1)-extractable P and K concentrations were used to monitor changes within the soils. Grain alone removed 13–15 kg ha –1 P and 15–18 kg ha –1 K each year, resulting in a cumulative removal of 70 and 85 kg ha –1 or 77 and 37% of the P and K fertilizer application, respectively. Harvesting stover increased nutrient removal such that when combined with grain removed, a cumulative total of 95% of the applied P and 126% of fertilizer K were taken away. This caused M1 P and K levels to decline significantly in the first year and even with annual fertilization to remain relatively static thereafter. For these Ultisols, we conclude that P and K fertilizer recommendations should be fine-tuned for P and K removed with grain and stover harvesting and that stover harvest of >50% by weight will significantly decrease soil test M1 P and K contents.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data-Informed Synthetic Networks of Water Distribution Systems for Resilience Analysis in Puerto Rico

The increasing potential of infrastructure disruptions calls for high-quality infrastructure models to be used in resilience analysis and decision making. Unfortunately, many utilities and communities do not have access to accurate and detailed models due to a lack of data and resources. Furthermore, security restrictions on sharing infrastructure models present roadblocks to research, analysis, and decision making. Recent advances in the development of synthetic water distribution models provide a potential solution to this problem. There is an opportunity to improve these methods by leveraging incomplete pipe datasets to aid synthetic network generation. To address this gap, we developed a methodology for synthetic network generation that incorporates partial pipe data using a modification of the minimum cost flow algorithm for network generation and pipe sizing. This methodology demonstrates how partial pipe data can be leveraged to improve site-specific synthetic network generation. For the study area of Mayagüez, Puerto Rico, a synthetic model generated using 50% of real pipe data matches the pressure of the validation system with an average error of 23.5 m of head, which improves upon the average error of 31.6 m of head produced by a synthetic model generated using no data of the real pipes. Additionally, synthetic networks are shown to replicate the pressure response under a disruption scenario of the validation network, suggesting potential use in resilience analysis.

resilience analysis↗
NASA NTRS1994

Three stages during the evolution of the genetic code

A diversification of the genetic code based on the number of codons available for the proteinous amino acids is established. Three groups of amino acids during evolution of the code are distinguished. On the basis of their chemical complexity and a small codon number those amino acids emerging later in a translation process are derived. Both criteria indicate that His, Phe, Tyr, Cys and either Lys or Asn were introduced in the second stage, whereas the number of codons alone gives evidence that Trp and Met were introduced in the third stage. The amino acids of stage one use purines rich codons, thus purines have been retained in their third codon position. All the amino acids introduced in the second stage, in contrast, use pyrimidines in this codon position. A low abundance of pyrimidines during early translation is derived. This assumption is supported by experiments on non enzymatic replication and interactions of DNA hairpin loops with a complementary strand. A back extrapolation concludes a high purine content of the first nucleic acids which gradually decreased during their evolution. Amino acids independently available form prebiotic synthesis were thus correlated to purine rich codons. Conclusions on prebiotic replication are discussed also in the light of recent codon usage data.

Baumann, U.↗
NASA NTRS1993

Three stages in the evolution of the genetic code

A diversification of the genetic code based on the number of codons available for the proteinous amino acids is established. Three groups of amino acids during evolution of the code are distinguished. On the basis of their chemical complexity those amino acids emerging later in a translation process are derived. Codon number and chemical complexity indicate that His, Phe, Tyr, Cys and either Lys or Asn were introduced in the second stage, whereas the number of codons alone gives evidence that Trp and Met were introduced in the third stage. The amino acids of stage 1 use purine-rich codons, while all the amino acids introduced in the second stage, in contrast, use pyrimidines in the third position of their codons. A low abundance of pyrimidines during early translation is derived. This assumption is supported by experiments on non-enzymatic replication and interactions of hairpin loops with a complementary strand. A back extrapolation concludes a high purine content of the first nucleic acids, which gradually decreased during their evolution. Amino acids independently available from prebiotic synthesis were thus correlated to purine-rich codons. Implications on the prebiotic replication are discussed also in the light of recent codon usage data.

Review↗
NASA NTRS2014

Investigation of Bio-Regenerative Life Support and Trash-to-Gas Experiment on a 4-Month Mars Simulation Mission

Future crewed missions to other planets or deep space locations will require regenerative Life Support Systems (LSS) as well as recycling processes for mission waste. Constant resupply of many commodity materials will not be a sustainable option for deep space missions, nor will stowing trash on board a vehicle or at a lunar or Martian outpost. The habitable volume will decline as the volume of waste increases. A complete regenerative environmentally controlled life support system (ECLSS) on an extra-terrestrial outpost will likely include physico-chemical and biological technologies, such as bioreactors and greenhouse modules. Physico-chemical LSS do not enable food production and bio-regenerative LSS are not stable enough to be used alone in space. Mission waste that cannot be recycled into the bio-regenerative ECLSS can include excess food, food packaging, clothing, tape, urine and fecal waste. This waste will be sent to a system for converting the trash into high value products. Two crew members on a 120 day Mars analog simulation, in collaboration with Kennedy Space Centers (KSC) Trash to Gas (TtG) project investigated a semi-closed loop system that treated non-edible biomass and other logistical waste for volume reduction and conversion into useful commodities. The purpose of this study is to show how plant growth affects the amount of resources required by the habitat and how spent plant material can be recycled. Real-time data was sent to the reactor at KSC in Florida for replicating the analog mission waste for laboratory operation. This paper discusses the 120 day mission plant growth activity, logistical and plant waste management, power and water consumption effects of the plant and logistical waste, and potential energy conversion techniques using KSCs TtG technology.

Trash-to-Gas↗
NASA NTRS2014

Investigation of Bio-Regenerative Life Support and Trash-To-Gas Experiment on a 4 Month Mars Simulation Mission

Future crewed missions to other planets or deep space locations will require regenerative Life Support Systems (LSS) as well as recycling processes for mission waste. Constant resupply of many commodity materials will not be a sustainable option for deep space missions, nor will storing trash on board a vehicle or at a lunar or Martian outpost. The habitable volume will decline as the volume of waste increases. A complete regenerative environmentally controlled life support system (ECLSS) on an extra-terrestrial outpost will likely include physico-chemical and biological technologies, such as bioreactors and greenhouse modules. Physico-chemical LSS do not enable food production and bio-regenerative LSS are not stable enough to be used alone in space. Mission waste that cannot be recycled into the bio-regenerative ECLSS can include excess food, food packaging, clothing, tape, urine and fecal waste. This waste will be sent to a system for converting the trash into the high value products. Two crew members on a 120 day Mars analog simulation, in collaboration with Kennedy Space Centers (KSC) Trash to Gas (TtG) project investigated a semi-closed loop system that treated non-edible biomass and other logistical waste for volume reduction and conversion into useful commodities. The purposes of this study are to show the how plant growth affects the amount of resources required by the habitat and how spent plant material can be recycled. Real-time data was sent to the reactor at KSC in Florida for replicating the analog mission waste for laboratory operation. This paper discusses the 120 day mission plant growth activity, logistical and plant waste management, power and water consumption effects of the plant and logistical waste, and potential energy conversion techniques using KSCs TtG reactor technology.

trash to gas↗
NASA NTRS2019

Evaluation of a Commercial Surface Vorticity Flow Solver for the Modeling of Propeller-Wing Interaction

A commercially available surface vorticity flow solver’s ability to model propeller-wing interaction effects was evaluated. First, a study was conducted to determine solution sensitivity to simulation parameters. Then, a deflected slipstream experiment was replicated with an actuator disk and wing model. Comparison with experimental data showed that predictions of lift and longitudinal force coefficients matched well at low flap deflections, but experienced offsets in magnitude with increasing flap deflection. Predictions of pitching moment differed significantly from experimental data largely due to the simple actuator disk model being insufficient for capturing the effects of non-zero flow incidence and non-uniform inflow.

Fei, Xiaofan↗
DOE OSTI2020

Multiplexed binary assembly and quantitative tracking of bacterial populations

Compositions and methods for tracking combinations of mutations in populations by coupling DNA assembly and paired-end sequencing technology with high-throughput sequencing. This allows for an unlimited number of mutation sites in a population of microorganisms to be identified, and allows sites to be sequenced across several replicates. Unique identifiers (DNA barcodes) can be used to measure fitness data by sequencing of the barcodes multiplexed with the mutation sites with high-throughput short sequencing read technology, allowing selections to be rapidly performed on populations of known combinatorial genotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Consideration for the application of artificial neural networks to criticality code validation - 14270

The artificial neural network (ANN) is a consistent example for non-parametric parameter estimation and regression, with powerful universal approximation properties, that is distribution independent. ANN application to criticality code validation centers on aligning mathematical relationships between code validation parameters and neural network prediction for those parameter values. Two specific goals are: (1) an appropriate ANN architecture to determine validation parameter values, and (2) bootstrapping individual ANNs as a 'Prediction Interval' (PI) technique to estimate the Calculation Margin and Upper Subcritical Limit. The individual ANN workflow is segregated into Training, Validation (network), and Testing Sets, where the network predictive properties and performance are expressed in the latter set. The Bootstrap ANN replicates a large set of individual ANNs (taken from the original data distribution) where (1-α/2)100% PI estimates can be determined. Results from the ANN method are compared to a variety of validation examples: a 'toy example' from ANSI/ANS-8.24, Appendix D, a variety of methods noted in a Nuclear Criticality Safety Division 2009 paper, and several validation campaigns for highly enriched uranium and plutonium systems. The ANN method is robust and can be applied to single or multivariate inputs. A trained ANN can provide both an average estimate (e.g., single value) and an estimate over a range of independent variable values where the kUSL can be formed in a regression relationship suitable for extrapolation. The input dependence has been tested, ranging from 15 to over 400 sample size distributions. An expanded Shapiro-Wilk test (for sample sizes up to 5000) was implemented to confirm that the ANN method is transparent to distribution function. The Principle Component Analysis method was applied as an input preprocessing step embedded within the ANN in order to reduce dimensionality and correlation for multivariable inputs. This can potentially aid in determining accurate margins over applying arbitrary margins. The automatic optimization of the Bootstrap ANN PI is left for future consideration. (authors)

42 ENGINEERING↗
DOE OSTI2014

Reduced evolutionary rates in HIV-1 reveal extensive latency periods among replicating lineages

Background HIV-1 can persist for the duration of a patient's life due in part to its ability to hide from the immune system, and from antiretroviral drugs, in long-lived latent reservoirs. Latent forms of HIV-1 may also be disproportionally involved in transmission. Thus, it is important to detect and quantify latency in the HIV-1 life cycle. Results We developed a novel molecular clock–based phylogenetic tool to investigate the prevalence of HIV-1 lineages that have experienced latency. The method removes alternative sources that may affect evolutionary rates, such as hypermutation, recombination, and selection, to reveal the contribution of generation-time effects caused by latency. Our method was able to recover latent lineages with high specificity and sensitivity, and low false discovery rates, even on relatively short branches on simulated phylogenies. Applying the tool to HIV-1 sequences from 26 patients, we show that the majority of phylogenetic lineages have been affected by generation-time effects in every patient type, whether untreated, elite controller, or under effective or failing treatment. Furthermore, we discovered extensive effects of latency in sequence data ( gag, pol , and env ) from reservoirs as well as in the replicating plasma population. To better understand our phylogenetic findings, we developed a dynamic model of virus-host interactions to investigate the proportion of lineages in the actively replicating population that have ever been latent. Assuming neutral evolution, our dynamic modeling showed that under most parameter conditions, it is possible for a few activated latent viruses to propagate so that in time, most HIV-1 lineages will have been latent at some time in their past. Conclusions These results suggest that cycling in and out of latency plays a major role in the evolution of HIV-1. Thus, no aspect of HIV-1 evolution can be fully understood without considering latency - including treatment, drug resistance, immune evasion, transmission, and pathogenesis.

Virology↗
DOE OSTI2023

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Multilayer X-ray mirrors - Interfacial roughness, scattering, and image quality

Scattering of the multilayer coatings used for our normal incidence soft X-ray telescope at a wavelength of 63.5 A has been measured at 1.54 A and grazing angles of incidence and at soft X-rays near normal incidence. Furthermore, the edge of the moon is used as a known test target to estimate the amount of scattering in the arcsec range from images obtained on the date of the solar eclipse on July 11, 1991. The internal surfaces of the coating are inspected by high-resolution electron microscopy. A theoretical model describing the evolution and replication of roughness from layer to layer throughout the structure, which is in agreement with all experimental data, is presented. We find that practically all roughness caused by the growth of the multilayer structure occurs at spatial frequencies which are too high to produce scattering. The substrate roughness is replicated at lower spatial frequencies which might produce scattering within the field of view of an instrument. However, roughness in this range is below the 0.5 A level, again resulting in insignificant amounts of scatter.

Spiller, Eberhard↗
NASA NTRS2018

Buoyancy Effects on Concurrent Flame Spread Over Thick PMMA

The flammability of combustible materials in a spacecraft is important for fire safety applications because the conditions in spacecraft environments differ from those on earth. Experimental testing in space is difficult and expensive. However, reducing buoyancy by decreasing ambient pressure is a possible approach to simulate on-earth the burning behavior inside spacecraft environments. The objective of this work is to determine that possibility by studying the effect of pressure on concurrent flame spread, and by comparison with microgravity data, observe up to what point low-pressure can be used to replicate flame spread characteristics observed in microgravity. Specifically, this work studies the effect of pressure and microgravity on upward/concurrent flame spread over 10 mm thick polymethyl methacrylate (PMMA) slabs. Experiments in normal gravity were conducted over pressures ranging between 100 and 40 kPa and a forced flow velocity of 200 mm/s. Microgravity experiments were conducted during NASA’s Spacecraft Fire Experiment (Saffire II), on board the Cygnus spacecraft at 100 kPa with an air flow velocity of 200 mm/s. Results show that reductions of pressure slow down the flame spread over the PMMA surface approaching that in microgravity. The data is correlated in terms of a non-dimensional mixed convection analysis that describes the convective heat transferred from the flame to the solid, and the primary mechanism controlling the spread of the flame. The extrapolation of the correlation to low pressures predicts well the flame spread rate obtained in microgravity in the Saffire II experiments. Similar results were obtained by the authors with similar experiments with a thin composite cotton/fiberglass fabric (published elsewhere). Both results suggest that reduced pressure can be used to approximately replicate flame behavior of untested gravity conditions for the burning of thick and thin solids. This work could provide guidance for potential ground-based testing for fire safety design in spacecraft and space habitats.

Environmental conditions↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
DOE OSTI2026

CONTROL AND DATA ACQUISITION IN A CYBER-PHYSICAL MIDSTREAM TESTBED

This thesis presents the development of a laboratory-scale cyber–physical midstream pipeline testbed designed to address this gap and support research in industrial control systems security. The platform integrates pumps, valves, sensors, programmable logic controllers (PLCs), and a human–machine interface (HMI) to emulate the monitoring and control architecture of real pipeline operations. The physical process is implemented as a closed-loop liquid circulation system designed to replicate flow behavior characteristic of midstream pipeline infrastructure. The testbed enables real-time data acquisition of key process variables, including flow rate and pressure facilitating the generation of datasets representative of normal pipeline operation. A threat model encompassing common ICS attack vectors was developed, including sensor spoofing, command injection, false data injection, denial-of-service attacks, and relay manipulation. Multiple attack scenarios were implemented and evaluated to demonstrate how cyber intrusions targeting sensors, actuators, networks, and software propagate into measurable physical consequences in pipeline flow and pressure. The developed platform serves as a practical, cost-effective environment for experimentation, education, and future cybersecurity research in midstream pipeline systems.

42 ENGINEERING↗