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DOE OSTI2022

Physical solvents and techno-economic analysis for pre-combustion CO 2 capture: A review

In this manuscript we review the use, development, and economic performance of physical solvents for pre-combustion CO 2 capture from high pressure H 2 rich syngas streams. Commercially available physical solvents are presented, followed by an assessment of the ideal properties that are important for development of novel solvents for CO 2 capture from high-pressure syngas streams. To compare the technical and economic performance of traditional and novel physical solvents, a review of the methods, assumptions and models used in techno-economic analysis (TEA) studies was conducted. It was found that, although some novel solvents show promising technical performance in the laboratory (e.g., high CO 2 absorption capacity and low vapor pressure), other issues (e.g., solvent viscosity and cost) may limit their industrial applications. Process simulations were useful tools for modeling the technical performance of processes using traditional and novel solvents. However, model predictions are most reliable when the methods and correlations used to develop the process simulation are validated with representative experimental data, in particular highly accurate baseline models are required for fair comparison among physical solvents. The key inputs and assumptions in pre-combustion CO 2 capture TEAs have also been summarized. Some studies showed that the promising technical performance of novel physical solvents can be offset by the high and often unknown costs of these solvents. Future development of novel physical solvents for pre-combustion CO 2 capture will benefit from more studies that conduct in-depth techno-economic analysis, specifically with validated process simulations and transparent economic models.

42 ENGINEERING↗

DOE OSTI2024

Parameter extraction approaches for compact modeling of thermoelectric modules

Thermoelectric (TE) cooling has experienced rapid advancements with the foundational understanding of TE materials. TE modules, compact and lightweight devices, have become the prevalent approach for implementing TE technologies. Accurately quantifying TE physical parameters (Seebeck coefficient α, thermal conductivity κ, and thermal resistance ρ) is challenging due to the dynamic temperature changes in operation. Furthermore, extracting lumped property parameters is crucial for designing energy systems using TE modules. Existing research has several limitations, such as lack of comparative analysis between prevalent formulae, reliance on potentially inaccurate vendor-supplied data, disregard for fundamental assumptions, and absence of empirical measurements. Further, this study addresses these gaps by conducting TE material characterization, comparing three existing formulae using vendor datasheets, designing a laboratory test facility for model validation and refinement, and outlining a structured data extraction procedure. The study's novelty lies in multiple key contributions: (1) a detailed comparative analysis of existing formulae for extracting TE property parameter; (2) executing experimental work in a laboratory setting to validate the model and elucidate its limitations; (3) highlighting potential risks; (4) clarifying possible assumptions from both material and engineering perspectives; and (5) considering temperature differential impacts. This comprehensive approach addresses the current research gaps and provides valuable insights into the design and application of TE modules in various energy systems.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A Physically-Based Model for Thermo-Oxidative and Hydrolytic Aging of Elastomers

A computationally efficient model is proposed to capture the loss of mechanical performance due to chemical aging that are formed as the competition of chain scission and cross-link formation/dissolution, such as thermo-oxidative aging or hydrolytic aging. The model should be considered an extension of our recent models [1, 2, 3] which further simplifies the matrix behavior based on the assumption of independence of environmental and mechanical damage. The model uses this assumption to reduce the necessary material parameters needed to model constitutive and inelastic behavior of elastomers during aging. To this end, the model can provide accurate predictions of the material performance with the significantly fewer number of fitting parameters. The model is relevant for all decay mechanisms formed by the occurrence of two simultaneous micro-mechanisms; (i) formation/reduction of the cross-links, and (ii) chain scission, both of which are present in thermo-oxidation and hydrolytic aging. Assuming the alteration of the chain density along the aging trajectory is identical to the peroxide cross-link density for thermo-oxidation, and the change of the average molecular weight for hydrolysis, the strain energy of polymer matrix can be rewritten as a function of deformation, deformation history, storage time and aging temperature. Next, the modified network alteration model is formulated for implementation into Finite Element (FE) simulations. The model is built on the presumption of homogeneous and consistent oxygen/water absorption and thus is mainly relevant for relatively thin samples exposed to environmental loads for a long time. The proposed model includes only six physically inspired material parameters. Therefore, while it is computationally efficient, it shows good agreement with own experimental data, which performed on various range of accelerated aging temperatures and times. With respect to its computational efficiency, simplicity, accuracy, and interpret-ability, the model is the right choice for advanced implementations in FE programs.

42 ENGINEERING↗

DOE OSTI2024

Site heterogeneity and broad surface-binding isotherms in modern catalysis: Building intuition beyond the Sabatier principle

Learning the science of heterogeneous catalysis and electrocatalysis always starts with the simple case of a flat, uniform surface with an ideal adsorbate. It has of course been recognized for a century that real catalysts are more complicated. For the increasingly complex catalysts of the 21st century, this Perspective argues that surface heterogeneity and non-ideal binding isotherms are central features, and their implications need to be incorporated in current thinking. A variety of systems are described herein where catalyst complexity leads to broad, non-Langmuirian surface isotherms for the binding of hydrogen atoms – and this occurs even for ideal, flat Pt(111) surfaces. Modern catalysis employs nanoscale materials whose surfaces have substantial step, edge, corner, impurity, and other defect sites, and they increasingly have both metallic and non-metallic elements M n X m , including metal oxides, chalcogenides, pnictides, carbides, doped carbons, etc. The surfaces of such catalysts are often not crystal facets of the bulk phase underneath, and they typically have a variety of potential active sites. Catalytic surfaces in operando are often non-stoichiometric, amorphous, dynamic, and impure, and often vary from one part of the surface to another. Understanding of the issues that arise at such nanoscale, multi-element catalysts is just beginning to emerge. Yet these catalysts are widely discussed using Brønsted/Bell-Evans-Polanyi (BEP) relations, volcano plots, Tafel slopes, the Butler-Volmer equation, and other linear free energy relations (LFERs), which all depend on the implicit assumption that the active sites are “similar” and that surface adsorption is close to ideal. These assumptions underly the ubiquitous intuition based on the Sabatier Principle, that the fastest catalysis will occur when key intermediates have free energies of adsorption that are not too strong nor too weak. Current catalysis research often aims to minimize the complexity of non-ideal isotherms through experimental and computational design (e.g., the use of single crystal surfaces), and these studies are the foundation of the field. In contrast, this Perspective argues that the heterogeneity of binding sites and binding energies is an inherent strength of these catalysts. Here, this diversity makes many nanoscale catalysts inherently a high-throughput screen wrapped in a tiny package. Only by making the heterogeneity part of the foundation of catalysis models, sorting the types of active sites and dissecting non-ideal binding isotherms, will modern catalysis learn to harness the inherent diversity of real catalysts. Controlling and exploiting diversity rather than avoiding it will help to optimize complex modern catalysts and catalytic conditions.

Mayer, James M.↗

DOE OSTI2020

A review of spatial Markov models for predicting pre-asymptotic and anomalous transport in porous and fractured media

Heterogeneity across a broad range of scales in geologic porous media often manifests in observations of non-Fickian or anomalous transport. While traditional anomalous transport models can successfully make predictions in certain geological systems, increasing evidence suggests that assumptions relating to independent and identically distributed increments constrain where and when they can be reliably applied. A relatively novel model, the Spatial Markov model (SMM), relaxes the assumption of independence. The SMM belongs to the family of correlated continuous time random walks and has shown promise across a wide range of transport problems relevant to natural porous media. It has been successfully used to model conservative as well as more recently reactive transport in highly complex flows ranging from pore scales to much larger scales of interest in geology and subsurface hydrology. In this review paper we summarize its original development and provide a comprehensive review of its advances and applications as well as lay out a vision for its future development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A novel energy balance approach for a verifiable and accurate solution of radiation extinction in purely absorbing particle clouds

Here we consider the problem of radiation transport through purely absorbing particle clouds. The gold-standard solution of particle-resolved Monte Carlo ray-tracing method to this problem is computationally expensive and therefore solving the radiation transport equation (specifically, the Beer-Bouguer law (BB-law)) on a Eulerian mesh is often preferred. While the absorption coefficient in the real problem is infinite, the BB-law approximates it to be a finite number in the form of number density through a set of assumptions. For particle clouds that do not obey these assumptions, the BB-law predicts an incorrect exponential decay. Also, when the number density is computed using the nearest-neighbor approach, the BB-law solution diverges when the Eulerian mesh size becomes closer to or smaller than the particle size. This numerical divergence is due to the homogenization error. Although the filtering strategy for number density minimizes the homogenization error, it still converges to an incorrect exponential decay for particle clouds that break the BB-law constraints and the cost of the filtering is equivalent to that of the gold-standard solution. In this study, we develop a novel, highly accurate, verifiable and cost-effective solution to the radiation transport equation on a Eulerian domain using an energy balance approach where we derive an expression for the absorption coefficient as a function of particle and Eulerian mesh sizes. We apply our new method to Poisson and turbulent particle clouds that violate all the BB-law constraints and show that the solution is converging upon the mesh refinement, and eventually, we recover the same gold-standard solution for a much cheaper computational cost.

42 ENGINEERING↗

DOE OSTI2024

In-situ determination of strain during transient burst testing and the temperature dependence of Zircaloy-4 claddings

Understanding fuel system behavior during postulated loss-of-coolant accidents is pertinent for continued safe and efficient operation of light water reactors, particularly as higher burnups are being pursued and safety margins re-evaluated. Conventional mechanical models for the incumbent Zr alloys typically rely on the assumption that steady-state creep is the dominant fuel cladding response during transient accident conditions. To investigate this assumption, simulated accident burst testing was performed on Zircaloy-4 claddings with balloon behavior measured in-situ. Here, two distinct loading conditions were utilized during burst testing: (1) constant-gas-inventory where pressure was allowed to increase with temperature and (2) constant pressure. In-situ strains and strain rates were measured via 2-dimensional digital image correlation techniques and synchronized with temperature to determine deformation dependencies. The temperature dependence of strain rate was characterized by a two segment Arrhenius relationship, with a distinct transition between the high and low temperature/strain regimes. The average activation energy of the lower temperature/strain regime was 328 ± 25 kJ/mol, in agreement with the ~320 kJ/mol used for conventional LOCA models. However, the higher temperature/strain segment, which encompassed most of ballooning, showed increased activation energies as well as a dependence on whether the burst region was in view. For tests that burst away from the camera view, the average high temperature/strain segment activation energy was 635 ± 150 kJ/mol. For samples where the rupture opening formed in view, the average activation energy was 1015 ± 179 kJ/mol. This observed shift in temperature dependence indicates a transition in deformation mechanism at the end of life, possibly to time independent failure mechanisms, which has not yet been visualized in the literature for Zr alloys. Parameters at the transition points were analyzed to determine thresholds for this change in behavior, which occurred at an average hoop strain of 6.9 ± 2.1 %.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Natural isotopic compositions of titanium, iron, and nickel observed in commercial fuel pellets – Promising candidate elements for stable isotope tagging

Stable isotope taggants would constitute unique identifiers for nuclear fuel cycle materials, resulting in expedited timelines and high confidence provenance assessments for nuclear forensics investigations. However, reliably identifying and interpreting stable isotope taggants in nuclear materials recovered from outside of regulatory control will largely be predicated on the assumption that the taggant element intrinsic to the untagged nuclear material exhibits natural isotopic ratios. Here, we present high-precision Ti, Fe, and Ni isotope compositions in 13 commercial low-enriched uranium (LEU) fuel pellets to assess the suitability of these transition metals as stable isotope taggants. Our investigations reveal limited isotope variations among the fuel pellets in all three elements, which are consistent with small mass-dependent isotope fractionations, comparable to variations previously reported for natural samples. In practice, isotopically tagged nuclear materials are expected to fall along isotopic mixing lines, since intrinsic background levels of taggant elements dilute the taggant towards natural isotope compositions. Furthermore, the observation that Ti, Fe, and Ni isotope compositions in a suite of LEU fuel pellets are close to or indistinguishable from estimates for the Bulk Silicate Earth demonstrates that a two end-member mixing assumption would be valid for these transition metals, indicating that all three are promising candidate elements for stable isotope tagging. Finally, we present mass balance calculations to quantify isotopic perturbations expected from admixing isotopically anomalous Ti, Fe, and Ni taggants to assess the interplay between elemental and taggant concentrations and find favorable compromises for facilitating successful taggant identification with current analytical methods.

Intentional forensics↗

DOE OSTI2023

System modeling for grid-interactive efficient building applications

Despite the abundance of research applications of system modeling in grid-interactive efficient buildings (GEBs), the transfer of those applications to real-world practices is still in its early stages. This is partially due to the lack of a summary on how system modeling should be established for a given application of GEBs. Here, we fill this gap by providing an extensive survey of the literature on system modeling for different GEBs that have been produced in the past decade. This survey involves over 300 relevant journal articles from the building community, the power system community, and the society of control. Specifically, we first identified key requirements of system modeling for GEBs based on various types of applications discussed in those publications. We then summarized the system modeling applications from those publications, in terms of their assumptions, modeling approach, and simulation. After that, we analyzed different assumptions made for various applications, the extent to which those modeling approaches satisfied the key requirements, and how those approaches can be scaled up for large-scale applications, which are quite common in GEBs. In addition, we gave insights on how to use system modeling for different applications in GEBs. At the end, we provided recommended directions for future studies to fully unleash the potentials of system modeling to support GEBs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Development of window scheduler algorithm exploiting natural ventilation and thermal mass for building energy simulation and smart home controls

Building energy simulations often rely on abstract assumptions when it comes to natural ventilation, such as ‘windows always open [or closed]’ or ‘windows open when outdoor temperature is below a certain threshold.’ However, simulations based on these assumptions fail to fully exploit the cooling potential of natural ventilation, as its effectiveness can be enhanced or diminished by various factors, including the presence of thermal mass. This issue also extends to smart home controls, where determining the window schedule becomes challenging without information about the building's response to outdoor conditions. To address these issues, this study has developed an analytical model for window operation schedules that leverages the passive cooling from natural ventilation. The analytical model was validated against a Modelica simulation. A case study utilizing the BESTEST model of ANSI/ASHRAE Standard 140 underwent validation with EnergyPlus simulations, showing strong concordance. The algorithm provides window schedule recommendations adapted to various airflow rates, thermal masses, and climate variations. Notably, the case study demonstrated that proper window scheduling could reduce indoor temperature by up to 8 °C under the given simulation settings, thereby improving resilience and indicating potential energy savings. Furthermore, the paper explores the potential opportunities and challenges this approach presents, especially for building simulation and smart home applications.

42 ENGINEERING↗

DOE OSTI2020

How fast can one resize a distributed file system?

Efficient resource utilization becomes a major concern as large-scale distributed computing infrastructures keep growing in size. Malleability, the possibility for resource managers to dynamically increase or decrease the amount of resources allocated to a job, is a promising way to save energy and costs. However, state-of-the-art parallel and distributed storage systems have not been designed with malleability in mind. The reason is mainly the supposedly high cost of data transfers required by resizing operations. Nevertheless, as network and storage technologies evolve, old assumptions about potential bottlenecks can be revisited. In this study, we evaluate the viability of malleability as a design principle for a distributed storage system. We specifically model the minimal duration of the commission and decommission operations. To show how our models can be used in practice, we evaluate the performance of these operations in HDFS, a relevant state-of-the-art distributed file system. We show that the existing decommission mechanism of HDFS is good when the network is the bottleneck, but can be accelerated by up to a factor 3 when storage is the limiting factor. We also show that the commission in HDFS can be substantially accelerated. With the highlights provided by our model, we suggest improvements to speed both operations in HDFS. We discuss how the proposed models can be generalized for distributed file systems with different assumptions and what perspectives are open for the design of efficient malleable distributed file systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Non-equilibrium simulations of hydraulic permeation: Role of mechanical boundary conditions in dense membranes

Understanding the mechanisms of water transport in reverse osmosis membranes is critical for improving membrane performance and guiding material design. While classical models describe transport as either solution-diffusion (SD)—involving concentration-driven diffusion through a homogeneous medium—or pore-flow (PF)—involving pressure-driven convection through percolated water channels—their applicability to crosslinked polyamide membranes remains debated. Here, using non-equilibrium molecular dynamics simulations, we investigate the impact of mechanical support conditions on pressure-driven water transport in polyamide membranes across varying crosslink densities and pressure differentials (1000–5000 bar). Two support conditions are considered: graphene-restrained, representing experimentally relevant supported membranes, and freeze-restrained, mimicking a self-supported structure. In graphene-restrained systems, water concentration gradients and constant pressure profiles emerge, consistent with SD theory and incompatible with PF assumptions due to the absence of percolated pores and sub-nanometer voids. In contrast, freeze-restrained systems display uniform water concentration and linearly decreasing pressure at 1000 bar, and exhibit compressibility-induced water gradients and partial percolation at 5000 bar, resembling PF-like behavior. However, the underlying assumptions of PF theory—continuous solvent pathways and pressure transmission through water-filled pores—are not met under most conditions. Our results demonstrate that accurate modeling of reverse osmosis membranes must incorporate realistic mechanical boundary conditions to distinguish between transport mechanisms. For dense polyamide membranes supported by porous substrates, graphene-restrained simulations best reflect experimental setups and support the SD model as the dominant mechanism of water permeation.

molecular dynamics↗

DOE OSTI2021

On the analysis of signal peaks in pulse-height spectra

The estimation of the signal location and intensity of a peak in a pulse height spectrum is important for X- ray and γ-ray spectroscopy, charged-particle spectrometry, liquid chromatography, and many other subfields. However, both the ‘‘centroid’’ and ‘‘signal intensity’’ of a peak in a pulse-height spectrum are ill-defined quantities and different methods of analysis will yield different numerical results. Here, we apply three methods of analysis. Method A is based on simple count summation and is likely the technique most frequently applied in practice. The analysis is straightforward and fast, and does not involve any statistical modeling. We find that it provides reliable results only for high signal-to-noise data, but has severe limitations in all other cases. Method B employs a Bayesian model to extract signal counts and centroid from the measured total and background counts. The resulting values are derived from the respective posteriors and, therefore, have a rigorous statistical meaning. The method makes no assumptions about the peak shape. It yields reliable and relatively small centroid uncertainties. However, it provides relatively large signal count uncertainties. Method C makes a strong assumption regarding the peak shape by fitting a Gaussian function to the data. Furthermore, the fit is based again on a Bayesian model. Although Method C requires careful consideration of the Gaussian width (usually given by the detector resolution) used in the fitting, it provides reliable values and relatively small uncertainties both for the signal counts and the centroid.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

The Primary Interaction Compton Couple algorithm for sorting GRETINA/GRETA interaction points

The Primary Interaction Compton Couple (PICC) algorithm is presented in this work. The algorithm is used to determine the first-interaction-point position for $γ$-ray events in GRETINA. The first-interaction-point position is crucial for in-beam $γ$-ray spectroscopy experiments with fast beams due to the effect of Doppler broadening on the in-beam energy resolution. The development of the algorithm and its performance compared to a tracking algorithm and the Main Interaction assumption is presented. The PICC algorithm is demonstrated with real data to outperform the $γ$-ray energy tracking algorithm used for comparison here and the Main Interaction assumption in first-interaction-point determinations.

GRETINA↗

DOE OSTI2023

Constraints on the Higgs boson self-coupling from single- and double-Higgs production with the ATLAS detector using $pp$ collisions at $\sqrt{s}$ = 13 TeV

Constraints on the Higgs boson self-coupling are set by combining double-Higgs boson analyses in the $b\overline{b}$$b\overline{b}$, $b\overline{b}$$τ^+$$τ^–$ and $b\overline{b}$$γγ$ decay channels with single-Higgs boson analyses targeting the $γγ$, $\overline{Z}$$\overline{Z}$$^*$, $WW^*$, $τ^+$$τ^–$ and $b\overline{b}$ decay channels. The data used in these analyses were recorded by the ATLAS detector at the LHC in proton–proton collisions at $\sqrt{s}$ = 13 TeV and correspond to an integrated luminosity of 126–139 fb –1 . The combination of the double-Higgs analyses sets an upper limit of $μ_{HH}$ < 2.4 at 95% confidence level on the double-Higgs production cross-section normalised to its Standard Model prediction. Combining the single-Higgs and double-Higgs analyses, with the assumption that new physics affects only the Higgs boson self-coupling ($λ_{HHH}$), values outside the interval –0.4 < $κ_λ$ = ($λ_{HHH}$/${λ}_{HHH}^{SM}$) < 6.3 are excluded at 95% confidence level. The combined single-Higgs and doubleHiggs analyses provide results with fewer assumptions, by adding in the fit more coupling modifiers introduced to account for the Higgs boson interactions with the other Standard Model particles. In this relaxed scenario, the constraint becomes –1.4 < $κ_λ$ < 6.1 at 95% CL.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Constraints on the Higgs boson self-coupling from the combination of single and double Higgs boson production in proton-proton collisions at $\sqrt{s} = 13$ TeV

The Higgs boson (H) trilinear self-coupling, λ 3 , is constrained via its measured properties and limits on the HH pair production using the proton-proton collision data collected by the CMS experiment at $\sqrt{s} = 13$ TeV . The combination of event categories enriched in single-H and HH events is used to measure κ λ , defined as the value of λ 3 normalized to its standard model prediction, while simultaneously constraining the Higgs boson couplings to fermions and vector bosons. Values of κ λ outside the interval -1.2 < κ λ < 7.5 are excluded at 2σ confidence level, which is compatible with the expected range of -2.0 < κ λ < 7.7 under the assumption that all other Higgs boson couplings are equal to their standard model predicted values. Relaxing the assumption on the Higgs couplings to fermions and vector bosons the observed (expected) κ λ interval is constrained to be within -1.4 < κ λ < 7.8 (-2.3 < κ λ < 7.8) at 2σ confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Constraint on the total width of the Higgs boson from Higgs boson and four-top-quark measurements in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This Letter presents a constraint on the total width of the Higgs boson (Γ H ) using a combined measurement of on-shell Higgs boson production and the production of four top quarks, which involves contributions from off-shell Higgs boson-mediated processes. This method relies on the assumption that the tree-level Higgs-top Yukawa coupling strength is the same for on-shell and off-shell Higgs boson production processes, thereby avoiding any assumptions about the relationship between on-shell and off-shell gluon fusion Higgs production rates, which were central to previous measurements. The result is based on up to 140 fb -1 of proton–proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV collected with the ATLAS detector at the Large Hadron Collider. The observed (expected) 95% confidence level upper limit on Γ H is 450 MeV (75 MeV). Additionally, considering the constraint on the Higgs-top Yukawa coupling from loop-induced Higgs boson production and decay processes further yields an observed (expected) upper limit of 160 MeV (55 MeV).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Data trustworthiness signatures for nuclear reactor dynamics simulation

With the increased reliance on digitization in industrial control systems, the need for effective monitoring techniques has risen dramatically. Specifically, there is now a growing concern about the so-called false data injection (FDI) attacks. These attacks aim to alter the raw sensors’ data to cause malicious outcomes. Any serious FDI algorithm is based on an intimate knowledge of the system and its associated physics models, which renders conventional outlier/anomaly detection techniques almost obsolete in the face of such attacks. Thus, a critical need has emerged to develop a new class of defense methods that are capable of detecting FDI attacks under the assumption that the attacker has a strong familiarity with the system and its physics modeling. This class of defense methods are denoted by model-based defenses which are premised on the assumption that the attacker, while having a good understanding of the system, does not have full privileged access to all proprietary data and historical records of operation. However, (s)he is assumed to be capable of learning system behavior using self-learning techniques during an initial lie-in-wait period. To defend against this scenario, we propose a new model-based randomized window algorithm that searches time-series data for signatures that can serve as classifiers between normal and FDI scenarios. The classifiers are based on the correlations between the dominant degrees of freedom (DOFs) and the less-dominant DOFs (expected to be very sensitive to the system details that are unknown to the attacker). For demonstration, RELAP5 models are employed to calculate representative nuclear reactor behavior during a number of transient scenarios. Finally, falsified data are injected into the RELAP5-simulated behavior, and the proposed signature-identification algorithm is employed to detect the injected data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗