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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Seasonal and Interspecific Variation in Frugivory by a Mixed Resident-Migrant Overwintering Songbird Community

Many temperate passerine bird species switch from diets of mostly invertebrates in the spring and summer to diets that include fruit and seeds in the fall and winter. However, relatively few studies have quantified diet composition or the extent of seasonal shifts during the non-breeding period, particularly among species and across communities with both residents and migrants. We measured carbon and nitrogen stable isotope values in food items (fruits, C3 and C4 seeds, and insects from various trophic levels and plant communities) and in multiple tissues (feathers and plasma/whole blood) from 11 species of songbirds wintering in the southeastern U.S. We combined these diet and tissue values with empirically derived discrimination factors and used concentration-dependent mixing models to quantify seasonal diet shifts. We also validated mixing model results with data from fecal samples. Diets in this bird community, as delineated N and C isotopic space, diverged in the fall and winter relative to the summer as consumption of fruits and seeds increased. Across this songbird community, estimated contributions of fruit to plasma/whole blood increased from 16.2 ± 7.5% in the fall (mean ± SD; range: 4–26%) to 21.7 ± 10.3% (range: 9–37%) in the winter, while contributions of seeds increased from 29.4 ± 2.6% (range: 28–32%) in the fall to 36.6 ± 4.8% (range: 32–42%) in the winter. Fecal data showed qualitatively similar trends to mixing models, but consistently estimated higher contributions of fruit. Our work indicates that fruits and seeds constitute substantial sources of sustenance for non-breeding songbirds, there is considerable separation of resource use among species in the fall and winter, and fecal estimates of contributions to songbird tissues should be interpreted cautiously.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Free Energies of Proton-Coupled Electron Transfer Reagents and Their Applications

Here, we present an update and revision to our 2010 review on the topic of proton- coupled electron transfer (PCET) reagent thermochemistry. Over the past decade, the data and thermochemical formalisms presented in that review have been of value to multiple fields. Concurrently, there have been advances in the thermochemical cycles and experimental methods used to measure these values. This Review (i) summarizes those advancements, (ii) corrects systematic errors in our prior review that shifted many of the absolute values in the tabulated data, (iii) provides updated tables of thermochemical values, and (iv) discusses new conclusions and opportunities from the assembled data and associated techniques. We advocate for updated thermochemical cycles that provide greater clarity and reduce experimental barriers to the calculation and measurement of Gibbs free energies for the conversion of X to XHn in PCET reactions. In particular, we demonstrate the utility and generality of reporting potentials of hydrogenation, E°(V vs H 2 ), in almost any solvent and how these values are connected to more widely reported bond dissociation free energies (BDFEs). The tabulated data demonstrate that E°(V vs H 2 ) and BDFEs are generally insensitive to the nature of the solvent and, in some cases, even to the phase (gas versus solution). This Review also presents introductions to several emerging fields in PCET thermochemistry to give readers windows into the diversity of research being performed. Some of the next frontiers in this rapidly growing field are coordination-induced bond weakening, PCET in novel solvent environments, and reactions at material interfaces.

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

We Just Want to Pump…You Up! Forecasting Grid-Connected Heat Pump Water Heater Energy Savings and Load Shifting Potential for the Southeast U.S.

Heat pump water heaters (HPWH) can achieve energy savings of 60-70% compared to conventional electric-resistance water heaters. However, even with a favorable simple payback period within the typical product lifetime, HPWHs make up only 1% of all electric water heaters sold in the residential sector. Market adoption is challenged, in part, by the lack of effective energy efficiency programs in the U.S. region with the greatest amount of residential electric water heaters. The recent integration of connected functionality into HPWHs offers the capability to shift load without undue negative impact on customers. This capability can provide value to utilities with peak load constraints, motivating them to promote HPWHs for the first time. This paper will present a methodology to forecast connected HPWH energy use and extrapolate load shifting potential for the Southeast U.S. region. The methodology leverages data from a robust connected HPWH field study conducted in the Pacific Northwest. A coefficient of performance (COP) relationship for HPWHs was developed using ambient and inlet water temperature data to forecast HPWH performance on a month-by-month basis. Using the forecasted COP, HPWH operating hours were calculated for meeting load, which serve as the proxy to extrapolate load shifting potential from the Pacific Northwest to the Southeast. As a use case, analytical results are presented for a specific utility. This methodology, in combination with market analysis, facilitates the development of customized energy savings and load shifting forecasts to understand the potential impacts of launching connected HPWH programs in specific utility service territories.

heat pump water heater, energy savings, load shift↗
DOE OSTI2026

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗
DOE OSTI2025

SEFOR Core I-E

This repository contains the VTB model developed for the Southwest Experimental Fast Oxide Reactor (SEFOR) core configuration I-E using the NEAMS tools. The MOOSE Reactor Module was employed to set up the geometry mesh, MC2-3 was applied to generate multigroup cross sections at various temperatures, and Griffin was used to calculate the k-eff values of Core I-E across these temperature conditions. To validate the deterministic results from Griffin, reference solutions were obtained with the Monte Carlo code Shift. The reactivity feedback was then derived and compared against SEFOR experimental data from isothermal tests in order to assess the performance of Griffin. Reproducing these results requires licensed access to several code systems, including Shift, Griffin, and MC2-3. Instructions for obtaining and accessing these codes can be found at the following locations: https://www.ornl.gov/scale/releases for SCALE/Shift, https://mooseframework.inl.gov/ncrc/applications/ncrc_root_griffin.html for Griffin, and https://www.anl.gov/nse/mc23 for MC2-3.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Gap-filled methane and carbon dioxide fluxes across two ecosystem states at the US-OWC AmeriFlux site (2015−2016, 2020−2022)

This dataset contains gap-filled measurements of methane flux (FCH4), net ecosystem CO2 exchange (NEE) partitioned into gross primary productivity (GPP) and ecosystem respiration (RE), as well as latent heat flux (LE) from a Great Lakes coastal freshwater wetland at the US-OWC AmeriFlux site. The dataset covers the peak growing seasons (June−September) of 2015−2016, dominated by Typha spp., and 2020−2022, characterized by floating-leaved species (lotus and water lily). These data were generated to investigate how rising water levels and vegetation shifts influence CH4 and CO2 fluxes across two distinct ecosystem states in this wetland. The dataset, provided in CSV format, includes half-hourly gap-filled flux data from June to September for 2015, 2016, 2020, 2021, and 2022. The gap-filled data refers to measurements where missing values due to instrument issues or quality control were filled using artificial neural networks (ANNs).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Historical and Future Global Irrigation Energy Consumption by Fuel and Region

Irrigation energy use is a significant component of agricultural production costs, contributing directly to the energy and emissions intensity of crop production and ultimately to food prices. Understanding the existing structure of irrigation energy consumption help achieve food-energy-water security and environmental goals. We present a comprehensive global data set detailing country-level irrigation energy consumption, emphasizing the comparative use of electric, diesel, and emerging solar pumps. To our knowledge, no such data set exists. We draw from a literature review to develop a logistic transformed regression model to estimate the shares of fuel sources for irrigation across countries over historical years to construct a global data set of country-level irrigation energy consumption by multiple fuel sources. Additionally, we compare our estimates of irrigation energy use with agricultural energy use as reported by the International Energy Agency and other external sources. We then use this data to project future irrigation energy use with the Global Change Analysis Model, which is a multisector dynamics model, to showcase the usage of this data set. Projections under the reference scenario show a global shift in fuel types for irrigation pumping, while patterns vary across regions, with India and Pakistan leading in solar-powered irrigation growth and countries like the USA and China continuing to rely primarily on grid electricity. This data set provides a resource to understand the role of irrigation fuel choices within the broader energy sector, as well as the connected agricultural, land use, and water sectors under alternative future scenarios, enabling informed decision making toward efficient agricultural practices.

Global Change Analysis Model (GCAM)↗
DOE OSTI2021

Unimolecular and bimolecular formic acid decomposition routes on dispersed Cu nanoparticles

The elementary steps and site requirements in formic acid (HCOOH) dehydrogenation on Cu surfaces remain of keen interest because formate species act as intermediates or spectators in methanol synthesis and water–gas shift reactions. Steady-state and transient kinetic data, isotopic effects, infrared spectra during catalytic and stoichiometric reactions, and theoretical treatments based on density functional theory (DFT) provide evidence for bimolecular reactions, in which saturated bidentate formate (*HCOO*) adlayers, present at 0.25 ML (0.25 *HCOO* per surface Cu atom), react with undissociated species (HCOOH$^\square$) bound at interstices within formate adlayers ($^\square$) to form H-bonded bimolecular HCOOH$^\square$-*HCOO* adducts. The co-existence of vicinal HCOOH$^\square$ and *HCOO* moieties is evident from antisymmetric infrared bands for *HCOO* that become stronger as a result of their H-bonding that perturbs the induced dipole moment of *HCOO* upon vibration, consistent with DFT-derived vibrational frequencies and intensities for such perturbed species. The *HCOO* moiety in this complex undergoes C-H activation via a transition state that is preferentially stabilized through H-bonding with the vicinal HCOOH$^\square$ relative to its *HCOO* precursor. DFT-derived HCOOH dehydrogenation activation barriers and those determined from the evolution of CO 2 from pre-adsorbed *HCOO* species are about 10 kJ mol -1 smaller in the presence of gaseous HCOOH reactants (because of HCOOH$^\square$-*HCOO* interactions) than those for the unimolecular decomposition of bound *HCOO* species. Such bimolecular routes are consistent with measured effects of HCOOH, H 2 , and CO pressures and of H/D isotopic substitution on dehydrogenation turnover rates and represent the predominant channel for the formation of CO 2 and H 2 during catalytic HCOOH dehydrogenation on Cu nanoparticles. A saturated *HCOO* adlayer that retains binding interstices and the presence of HCOOH(g) enable a sequence of elementary steps unavailable for *HCOO* species, thus circumventing unassisted unimolecular routes that exhibit higher activation barriers.

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

The Atlantic Jet Response to Stratospheric Events: A Regime Perspective

The tropospheric response to Sudden Stratospheric Warmings (SSWs) is associated with an equatorward shift in the midlatitude jet and associated storm tracks, while Strong Polar Vortex (SPV) events elicit a contrasting response. Recent analyses of the North Atlantic jet using probability density functions of a jet latitude index have identified three preferred jet latitudes, raising the question of whether the tropospheric response to SSWs and SPVs results from a change in relative frequencies of these preferred jet regimes rather than a systematic jet shift. We explore this question using atmospheric reanalysis data from 1979 to 2018 (26 SSWs and 33 SPVs), and a 202-years integration of the Whole Atmosphere Community Climate Model (92 SSWs and 68 SPVs). Following SSWs, the northern jet regime becomes less common and the central and southern regimes become more common. These changes occur almost immediately following “split” vortex events, but are more delayed following “displacement” events. In contrast, the northern regime becomes more frequent and the southern regime less frequent following SPV events. Following SSWs, composites of 500-hPa geopotential heights, surface air temperatures, and precipitation most closely resemble composites of the southern jet regime, and are generally opposite in sign to the composites of the northern jet regime. These comparisons are reversed following SPVs. Thus, one possible interpretation is that the two southernmost regimes appear to be favored following SSWs, while the southernmost regime becomes less common following SPVs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Anomalous temperature dependence of the experimental x-ray structure factor of supercooled water

The structural changes of water upon deep supercooling were studied through wide-angle x-ray scattering at SwissFEL. The experimental setup had a momentum transfer range of 4.5 Å-1, which covered the principal doublet of the x-ray structure factor of water. The oxygen–oxygen structure factor was obtained for temperatures down to 228.5 ± 0.6 K. Similar to previous studies, the second diffraction peak increased strongly in amplitude as the structural change accelerated toward a local tetrahedral structure upon deep supercooling. We also observed an anomalous trend for the second peak position of the oxygen–oxygen structure factor (q 2 ). We found that q 2 exhibits an unprecedented positive partial derivative with respect to temperature for temperatures below 236 K. Based on Fourier inversion of our experimental data combined with reference data, we propose that the anomalous q 2 shift originates from that a repeat spacing in the tetrahedral network, associated with all peaks in the oxygen–oxygen pair-correlation function, gives rise to a less dense local ordering that resembles that of low-density amorphous ice. The findings are consistent with that liquid water consists of a pentamer-based hydrogen-bonded network with low density upon deep supercooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Time-tagging data acquisition system for testing superconducting electronics based on an RFSoC and custom analog frontend

Novel electronic devices can often be operated in a plethoraof ways, which makes testing circuits comprised of them difficult.Often, no single tool can simultaneously analyze the operatingmargins, maximum speed, and failure modes of a circuit, particularlywhen the intended behavior of subcomponents of the circuit is notstandardized. This work demonstrates a cost-effective time-domaindata acquisition system for electronic circuits that enables moreintricate verification techniques than are practical withconventional experimental setups. We use high-speeddigital-to-analog converters and real-timemulti-gigasample-per-second waveform processing to push experimentalcircuits beyond their maximum operating speed. Our customtime-tagging data capture firmware reduces memory requirements andcan be used to determine when errors occur. The firmware iscombined with a thermal-noise-limited analog frontend with50 dB of dynamic range. Compared to currentlyavailable commercial test equipment that is seven times moreexpensive, this data acquisition system was able to operate asuperconducting shift register at a nearly three-times-higher clockfrequency (200 MHz vs. 80 MHz).

Foster, Reed A. [MIT] (ORCID:0000000231002127)↗
DOE OSTI2022

Photometric redshifts from SDSS images with an interpretable deep capsule network

ABSTRACT Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on ugriz images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of ∼400 000 Sloan Digital Sky Survey galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets (r ≤ 17.8 and zspec ≤ 0.4) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a two-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g. size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g. magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Proton decays in 16 Ne and 18 Mg and isospin-symmetry breaking in carbon isotopes and isotones

We report that proton-rich nuclei possess unique properties in the nuclear chart. Due to the presence of both continuum coupling and Coulomb interaction, phenomena such as halos, Thomas-Ehrman shift, and proton emissions can occur. Relevant experimental data are difficult to obtain, so that theoretical calculations are needed to understand nuclei at drip lines and to guide experimentalists. In particular, the 16 Ne and 18 Mg isotopes are supposed to be one-proton and/or two-proton emitting nuclei, but associated experimental data are either incomplete or even unavailable. Consequently, we performed Gamow shell model calculations of carbon isotones bearing A = 15 - 18 . Isospin-symmetry breaking occurring in carbon isotones and isotopes is also discussed. It is hereby shown that the mixed effects of continuum coupling and Coulomb interaction at drip lines generate complex patterns in isospin multiplets. Added to that, it is possible to determine the one-proton and two-proton widths of 16 Ne and 18 Mg . Obtained decay patterns are in agreement with those obtained in previous experimental and theoretical works. Moreover, to our knowledge, this is the first theoretical calculation of binding energy and partial decay widths of 18 Mg in a configuration interaction picture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Nitrogen starvation causes lipid remodeling in Rhodotorula toruloides

Abstract Background The oleaginous yeast Rhodotorula toruloides is a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited by R. toruloides under nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers. Results We performed a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Specifically, we performed comparative transcriptomic and lipidomic analysis of the oleaginous yeast under nitrogen-sufficient and nitrogen deficient conditions. Clustering analysis of transcriptomic data was used to identify the growth phase where nitrogen-deficient cultures diverged from the baseline conditions. Independently, lipidomic data was used to identify that lipid fractions shifted from mostly phospholipids to mostly storage lipids under the nitrogen-deficient phenotype. Through an integrative lens of transcriptomic and lipidomic analysis, we discovered that R. toruloides undergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. We identify specific mRNAs and pathways that are strongly correlated with an increase in lipid levels, thus identifying putative targets for engineering greater lipid accumulation in R. toruloides . One surprising pathway identified was related to inositol phosphate metabolism, suggesting further inquiry into its role in lipid accumulation. Conclusions Integrative analysis identified the specific biosynthetic pathways that are differentially regulated during lipid remodeling. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Probabilistic Reasoner Based on Bayes Risk for Damage Detection in Structural Systems

Structural health monitoring (SHM) systems are used to inform operation of structural systems subject to loads and environments that may affect their integrity. SHM systems rely on continuous monitoring of the structure to determine its health state. These systems are often coupled with a model of the deployed structure to determine the consequences of changes in the system by forecasting the response to future states. These models, which may be thought of as digital twins, need to be updated to reflect the latest state of the structural system. This work makes use of an uncertainty-aware machine learning model that enforces distance preservation of the original input space to determine deviations from the training data input space distributions. This workflow enables domain shift detection to determine whether damage is present in the structure. The uncertainty metrics generated by this network are then used in a Bayes risk framework to design an optimal damage detector given cost and risk considerations. The approach is demonstrated on a computational example with simulated damage.

Najera-Flores, David [ATA Engineering, Inc.]↗
DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for the preparation of model inputs and post-processing of outputs are also included. The model's predictive performance achieved a normalized Kling-Gupta Efficiency (KGE) of 0.81, surpassing SWAT without the necessity for site-specific calibration.The Amanzi-ATS model presented in this modeL-data archive allows for numerical experiments to explore the shifts in the flow structure under different drainage scenarios. As a tool for advancing the understanding of distributed hydrological responses and nutrient cycling, this archived model provides valuable insights for researchers, modelers, and decision-makers involved in watershed management and environmental modeling.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model, are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exponential Backoff and Its Security Implications for Safety-Critical OT Protocols over TCP/IP Networks

The convergence of Operational Technology (OT) and Information Technology (IT) networks has become increasingly prevalent with the growth of Industrial Internet of Things (IIoT) applications. This shift, while enabling enhanced automation, remote monitoring, and data sharing, also introduces new challenges related to communication latency and cybersecurity. Oftentimes, legacy OT protocols were adapted to the TCP/IP stack without an extensive review of the ramifications to their robustness, performance, or safety objectives. To further accommodate the IT/OT convergence, protocol gateways were introduced to facilitate the migration from serial protocols to TCP/IP protocol stacks within modern IT/OT infrastructure. However, they often introduce additional vulnerabilities by exposing traditionally isolated protocols to external threats. This study investigates the security and reliability implications of migrating serial protocols to TCP/IP stacks and the impact of protocol gateways, utilizing two widely used OT protocols: Modbus TCP and DNP3. Our protocol analysis finds a significant safety-critical vulnerability resulting from this migration, and our subsequent tests clearly demonstrate its presence and impact. A multi-tiered testbed, consisting of both physical and emulated components, is used to evaluate protocol performance and the effects of device-specific implementation flaws. Through this analysis of specifications and behaviors during communication interruptions, we identify critical differences in fault handling and the impact on time-sensitive data delivery. The findings highlight how reliance on lower-level IT protocols can undermine OT system resilience, and they inform the development of mitigation strategies to enhance the robustness of industrial communication networks.

DNP3↗