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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Double-Edged Sword: The Role of Prior Knowledge in Memory Aging

People accumulate knowledge throughout their lifespan and the accumulated knowledge influences how we encode and retrieve information in memory processing. This study aims to investigate the role of knowledge in associative memory across the adult lifespan, and specifically examines the effects of two material properties that interact with prior knowledge: congruency – whether the material is congruent with people’s prior knowledge, and ambiguity – whether the material is ambiguous to interpret based on prior knowledge. 273 participants (aged 22–70 years old) completed an incidental memory task online. Participants were shown pictures depicting an object in a scene and judged if the object was likely or unlikely to be in the particular scene. Later, in the recognition test, participants were asked to identify if the exact picture was presented earlier. The pictures were manipulated to have varying levels of congruency, meaning that some depicted likely object–scene pairs and some unlikely. We also measured how different the likely/unlikely judgment for each object–scene pair was across all participants to determine the ambiguity level of the object–scene pair: some were more likely to receive diverse responses across people, whereas others are unambiguously consistent (or inconsistent) with common knowledge shared by most people. We used mixed-effects logistic regressions to predict memory outcome for each trial as a function of age, age 2 , congruency/ambiguity, and their interactions. The object–scene pairs perceived as congruent had higher hit rates than incongruent ones, as well as higher false alarm rates, especially in middle-aged and older people. Higher ambiguity was also related to both greater true and false memory, independent of age. Finally, the effect of ambiguity only emerged when the object–scene pair was perceived incongruent. The results suggest that people rely on prior knowledge to process new information and that this reliance improves hit responses, but also induces false memories particularly for middle-aged and older people, suggesting a double-edged role of knowledge in associative memory and its disproportionate influence on memory aging. Over-reliance on knowledge in older adults, which has been suspected in other cognitive processes, may be one of the mechanisms underlying associative memory decrease in aging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A method for convex black-box integer global optimization

Here we study the problem of minimizing a convex function on a nonempty, finite subset of the integer lattice when the function cannot be evaluated at noninteger points. We propose a new underestimator that does not require access to (sub)gradients of the objective; such information is unavailable when the objective is a blackbox function. Rather, our underestimator uses secant linear functions that interpolate the objective function at previously evaluated points. These linear mappings are shown to underestimate the objective in disconnected portions of the domain. Therefore, the union of these conditional cuts provides a nonconvex underestimator of the objective. We propose an algorithm that alternates between updating the underestimator and evaluating the objective function. We prove that the algorithm converges to a global minimum of the objective function on the feasible set. We present two approaches for representing the underestimator and compare their computational effectiveness. We also compare implementations of our algorithm with existing methods for minimizing functions on a subset of the integer lattice. We discuss the difficulty of this problem class and provide insights into why a computational proof of optimality is challenging even for moderate problem sizes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A GPU-based Approach for Path Planning Optimization via Travel Length Reduction

Typically, before constructing an object with an additive manufacturing system, the 3D object must be sent through a process called slicing. Slicing converts a 3D object commonly in the form of an STL file into a set of layers by horizontally intersecting a plane with the object at various heights. At each height, called a layer, multiple 2D polygons can be generated. Each polygon represents a boundary for solid geometry and is called an island. Each island is then comprised of multiple path types in an attempt to optimally fill the polygon. To move between each island and each islands’ paths, travels are inserted. Travels are simply motion by the system to move from one area of construction to another. Travels do not contribute to the construction of the object, and so, are considered wasted motion. In large-scale additive manufacturing, objects can be quite large and the distance between islands can be large as well. As a result, these travels can waste a significant amount of time. Ideally, travels would be as short as possible, however, computing global minimal travel paths is computationally expensive. To combat this problem, researchers at Oak Ridge National Lab developed a GPU-based approach to travel insertion based on a unique factoradic representation. This representation was then utilized by the GPU to solve the Traveling Salesman Problem (TSP). This algorithm was able to compute global minimal travel paths quickly resulting in faster object construction. A general investigation was also carried out to determine when a GPU vs CPU implementation would be beneficial.

Borish, Michael↗
DOE OSTI2021

A Binomial Stochastic Framework for Efficiently Modeling Discrete Statistics of Convective Populations

Abstract Understanding the coupling between convective clouds and the general circulation, as well as addressing the gray zone problem in convective parameterization, requires insight into the genesis and maintenance of spatial patterns in cumulus cloud populations. In this study, a simple toy model for recreating populations of interacting convective objects as distributed over a two‐dimensional Eulerian grid is formulated to this purpose. Key elements at the foundation of the model include i) a fully discrete formulation for capturing discrete behavior in convective properties at small population sample sizes, ii) object age‐dependence for representing life‐cycle effects, and iii) a prognostic number budget allowing for object interactions and co‐existence of multiple species. A primary goal is to optimize the computational efficiency of this system. To this purpose the object birth rate is represented stochastically through a spatially aware Bernoulli process. The same binomial stochastic operator is applied to horizontal advection of objects, conserving discreteness in object number. The applicability to atmospheric convection as well as behavior implied by the formulation is assessed. Various simple applications of the BiOMi model (Binomial Objects on Microgrids) are explored, suggesting that important convective behavior can be captured at low computational cost. This includes i) subsampling effects and associated powerlaw scaling in the convective gray zone, ii) stochastic predator‐prey behavior, iii) the downscale turbulent energy cascade, and iv) simple forms of spatial organization and convective memory. Consequences and opportunities for convective parameterization in next‐generation weather and climate models are discussed.

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

Experimental study of multiple-orientation muon tomography with image optimization in sparse data environments

Due to the high penetrating power of cosmic-ray muons, they can be used to probe very thick and dense objects. As muons are charged particles, they can be tracked by ionization detectors, determining the position and direction of the muons. With detectors on either side of an object to measure particle direction change, scattering information within the object can be found. This can be used to produce a scattering-intensity image within the object related to density and atomic number. Such imaging is typically performed with a single detector-object orientation, taking advantage of the more intense downward flux of muons, producing planar imaging with some depth-of-field information in the third dimension. Several simulation studies were published with multiorientation tomography, which can form a three-dimensional representation faster than a single-orientation view. In this study, experimental muon-scatter-based tomography was performed using a concrete filled steel drum with several different metal wedges inside, with the drum between detector planes. Data were collected from different detector-object orientations by rotating the steel drum. The data collected from each orientation were combined using two different tomographic methods. A traditional inverse Radon transform approach used for computed tomography and a combination of multiple depth-of-field reconstructions were applied to the data. As cosmic-ray muon flux imaging is rate limited, the imaging techniques were compared for sparse data. Using the combined depth-of-field reconstruction technique, fewer detector-object orientations were needed to reconstruct images that could be used to differentiate the metal wedges.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗
DOE OSTI2022

NucMesh: nuclear reactor geometry creation and mesh generation module in NEMoSys

NucMesh is a parameterized geometry and mesh generator for nuclear reactors developed within the Nuclear Energy Modeling System NEMoSys at Illinois Rocstar. NEMoSys is a platform developed for mesh generation, adaptive refinement, and solution verification. NucMesh is implemented to be generalized and extensible with a robust computer aided design engine and multiple mesh generation algorithms for unstructured triangular, quad-dominant, and structured quadrilateral meshing. In this paper, we present the geometric and meshing features of NucMesh. Geometrically objects are constructed bottom-to-top and overlaps are addressed automatically. A sophisticated object tracking algorithm prevents data from being lost for segmented objects. We discuss the primitive objects of circle and polygons that constitute the module and show how they are used with example inputs. Arrays of primitives and arrays of arrays are utilized to build large assemblies of objects. The concept of saved objects is discussed to demonstrate how repetitive objects can be reused easily and augmented in place. Three dimensional meshes can be obtained through mesh extrusion where all materials and side sets are extended to three dimensions. We show that side sets can be defined nearly anywhere within the geometry and can then be applied to the mesh. Finally, example reactor meshes are demonstrated for the Idaho National Laboratory Advanced Test Reactor and Los Alamos National Lab Empire reactor, both of which use control drums that NucMesh handles easily. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

TA-55 Forensic Support Operations Cross-Training Exercise

As part of the annual FBI/LANL training schedule, a joint training exercise was conducted during the week of 10FEB2020 with FBI HEAT members and LANL Fissile Material Handlers (FMHs). The joint training exercise was conducted in a non-radiological area to reduce cost and ensure the test object would not be contaminated. The exercise test object was fabricated by LANL using surrogate materials to represent an object containing Special Nuclear Material (SNM). Working with Jim Blankenship and Kevin Swearingen, functional requirements of the test object included the following: unclassified, disassembly (to include screws), and moderately heavy. To meet the objectives, the test object was fabricated by welding a custom aluminum box (8” x 8” x 12”) with a lid which was secured by four (4) screws. The custom box housed a track and field shot put (16 lbs.) that was anchored by a hose clamp. The intent of the training was to disassemble the test object and conduct traditional forensic determinations on the parts. This lessons learned report documents all of the associated aspects related to the joint training effort.

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

Economic Evaluation of Modernization Expenditures for Electric Utility Distribution Systems: A Guide for Utility Regulators

Cost-effectiveness evaluation of potential grid modernization solutions is integral to integrated distribution system planning (IDSP). This report synthesizes and updates prior cost-effectiveness approaches identified by the U.S. Department of Energy for grid modernization investments, incorporating multi-objective decision-making. The structure of the report follows the IDSP process, from identifying objectives and priorities to prioritizing grid solutions. The report details two methods for conducting initial cost-effectiveness screening of individual and interdependent grid components: (1) Lowest Reasonable Cost and (2) Benefit-Cost Analysis. Drawing on solutions that passed the initial cost-effectiveness screen, the utility prioritizes grid solutions based on policy objectives and priorities, regulatory compliance, operational efficiencies, and other factors to develop a portfolio of distribution solutions. The utility uses multi-objective decision-making to assess each proposed expenditure against each objective and respective metric. The utility applies a weighting factor, reflecting the priority ranking of the objective, to the total numerical “score” based on the contribution of the proposed solution to addressing each objective. Ultimately, the utility ranks each expenditure from highest to lowest priority using the final score for each solution as well as its cost. The report includes examples of emerging best practices for states and utilities and a cost-effectiveness process checklist.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

From Modular ADMS to Plug-and-Play Ops: Distribution Grid Operations with Platform-Level Orchestration to Enable Ambitious App Hosting

The core function of the distribution grid is to provide electricity to consumers affordably, reliably, and securely. In pursuing these core objectives, distribution utilities are accountable to customers, regulators, and in some cases, shareholders. Other third parties such as aggregators and microgrids can also have a stake in the smooth operation of the grid. Each of these stakeholders has economic, business, and/or governance objectives that inform their expectations of the distribution grid. This multi-objective, multi-stakeholder environment creates tension that must be reconciled to successfully design and operate the distribution grid. Innovative companies are competing to bring high-tech solutions to electric utilities and their customers that address each of these objectives. Many developers of advanced distribution management systems (ADMS) and distributed energy resource management systems (DERMS) have adopted a modular architecture that allows grid operators to select functions and features according to their individual system needs. A modular platform also allows the solution provider to develop and integrate specific new product modules; however, the need to pursue multiple objectives with a fixed set of controllable devices makes integration expensive whether it is done at the product development stage or the deployment stage. This cost creates a significant barrier to adoption and can lengthen the product to market time of new solutions. To fundamentally address the complexity of system integration for distribution grid operations, the U.S. Department of Energy Office of Electricity has funded the GridAPPS-D project at PNNL, which streamlines integration by contributing to standards development, defining system architecture, applying advanced mathematics, and developing open-source software to demonstrate the concept of an open data-integration platform for distribution operations. The open data-integration platform concept enables system operators and solution providers to deploy ambitious, best-of-breed applications (or apps) without continually reengineering for integration. Ambitious apps developed by different solution providers will inevitably attempt to achieve different control objectives with the same set of controllable devices. If the open platform itself can resolve these conflicts in a way that achieves the best available outcomes for all apps, doesn’t restrict the ambitious design of apps, and ensures safe and secure operations, apps will be able to plug-and-play with the platform at the same time as other ambitious apps. In this paper, we describe a framework called App Deconfliction that empowers a platform to assign setpoints to controllable devices based on the values preferred by different apps (and even external stakeholder entities like customers or aggregators). The App Deconfliction framework is compatible with several methods for determining setpoint values. We present two methods based on game theory that provide a subtle built-in incentive structure for developers to adapt their apps to the fact that they will be operating in a moderated multi-app environment and to favor device setpoints that have the most effect on their objectives over those that have the least effect. Our simulation-based demonstrations have shown that game-theory-based deconfliction can lead to a 7% improvement in control space utilization compared to design-based methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Quantum Theory of the Classical: Einselection, Envariance, Quantum Darwinism and Extantons

Core quantum postulates including the superposition principle and the unitarity of evolutions are natural and strikingly simple. I show that—when supplemented with a limited version of predictability (captured in the textbook accounts by the repeatability postulate)—these core postulates can account for all the symptoms of classicality. In particular, both objective classical reality and elusive information about reality arise, via quantum Darwinism, from the quantum substrate. This approach shares with the Relative State Interpretation of Everett the view that collapse of the wavepacket reflects perception of the state of the rest of the Universe relative to the state of observer’s records. However, our “let quantum be quantum” approach poses questions absent in Bohr’s Copenhagen Interpretation that relied on the preexisting classical domain. Thus, one is now forced to seek preferred, predictable, hence effectively classical but ultimately quantum states that allow observers keep reliable records. Without such (i) preferred basis relative states are simply “too relative”, and the ensuing basis ambiguity makes it difficult to identify events (e.g., measurement outcomes). Moreover, universal validity of quantum theory raises the issue of (ii) the origin of Born’s rule, p k =|ψ k | 2 , relating probabilities and amplitudes (that is simply postulated in textbooks). Last not least, even preferred pointer states (defined by einselection—environment—induced superselection)—are still quantum. Therefore, unlike classical states that exist objectively, quantum states of an individual system cannot be found out by an initially ignorant observer through direct measurement without being disrupted. So, to complete the ‘quantum theory of the classical’ one must identify (iii) quantum origin of objective existence and explain how the information about objectively existing states can appear to be essentially inconsequential for them (as it does for states in Newtonian physics) and yet matter in other settings (e.g., thermodynamics). I show how the mathematical structure of quantum theory supplemented by the only uncontroversial measurement postulate (that demands immediate repeatability—hence, predictability) leads to preferred states. These (i) pointer states correspond to measurement outcomes. Their stability is a prerequisite for objective existence of effectively classical states and for events such as quantum jumps. Events at hand, one can now enquire about their probability—the probability of a pointer state (or of a measurement record). I show that the symmetry of entangled states—(ii) entanglement—assisted invariance or envariance—implies Born’s rule. Envariance also accounts for the loss of phase coherence between pointer states. Thus, decoherence can be traced to symmetries of entanglement and understood without its usual tool—reduced density matrices. A simple and manifestly noncircular derivation of p k =|ψ k | 2 follows. Monitoring of the system by its environment in course of decoherence typically leaves behind multiple copies of its pointer states in the environment. Only pointer states can survive decoherence and can spawn such plentiful information-theoretic progeny. This (iii) quantum Darwinism allows observers to use environment as a witness—to find out pointer states indirectly, leaving systems of interest untouched. Quantum Darwinism shows how epistemic and ontic (coexisting in epiontic quantum state) separate into robust objective existence of pointer states and detached information about them, giving rise to extantons—composite objects with system of interest in the core and multiple records of its pointer states in the halo comprising of environment subsystems (e.g., photons) which disseminates that information throughout the Universe.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Sensing Technology Survey for Obstacle Detection in Vegetation

This study reviews obstacle detection technologies in vegetation for autonomous vehicles or robots. Autonomous vehicles used in agriculture and as lawn mowers face many environmental obstacles that are difficult to recognize for the vehicle sensor. This review provides information on choosing appropriate sensors to detect obstacles through vegetation, based on experiments carried out in different agricultural fields. The experimental setup from the literature consists of sensors placed in front of obstacles, including a thermal camera; red, green, blue (RGB) camera; 360° camera; light detection and ranging (LiDAR); and radar. These sensors were used either in combination or single-handedly on agricultural vehicles to detect objects hidden inside the agricultural field. The thermal camera successfully detected hidden objects, such as barrels, human mannequins, and humans, as did LiDAR in one experiment. The RGB camera and stereo camera were less efficient at detecting hidden objects compared with protruding objects. Radar detects hidden objects easily but lacks resolution. Hyperspectral sensing systems can identify and classify objects, but they consume a lot of storage. To obtain clearer and more robust data of hidden objects in vegetation and extreme weather conditions, further experiments should be performed for various climatic conditions combining active and passive sensors.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

An Information Theory Approach on Deciding Spectroscopic Follow-ups

Classification and characterization of variable phenomena and transient phenomena are critical for astrophysics and cosmology. These objects are commonly studied using photometric time series or spectroscopic data. Given that many ongoing and future surveys are conducted in a time domain, and given that adding spectra provides further insights but requires more observational resources, it would be valuable to know which objects we should prioritize to have a spectrum in addition to a time series. We propose a methodology in a probabilistic setting that determines a priori which objects are worth taking a spectrum of to obtain better insights, where we focus on the insight of the type of the object (classification). Objects for which we query their spectrum are reclassified using their full spectral information. We first train two classifiers, one that uses photometric data and another that uses photometric and spectroscopic data together. Then for each photometric object we estimate the probability of each possible spectrum outcome. We combine these models in various probabilistic frameworks (strategies), which are used to guide the selection of follow-up observations. The best strategy depends on the intended use, whether it is obtaining more confidence or accuracy. For a given number of candidate objects (127, equal to 5% of the data set) for taking spectra, we improve the class prediction accuracy by 37% as opposed to 20% of a non-naive (non-random) best-baseline strategy. Our approach provides a general framework for follow-up strategies and can be extended beyond classification to include other forms of follow-ups beyond spectroscopy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

First experimental study of multiple orientation muon tomography, with image optimization in sparse data environments

Due to the high penetrating power of cosmic ray muons, they can be used to probe very thick and dense objects. As charged particles, they can be tracked by ionization detectors, determining the position and direction of the muons. With detectors on either side of an object, particle direction changes can be used to extract scattering information within an object. This can be used to produce a scattering intensity image within the object related to density and atomic number. Such imaging is typically performed with a single detector-object orientation, taking advantage of the more intense downward flux of muons, producing planar imaging with some depth-of-field information in the third dimension. Several simulation studies have been published with multi-orientation tomography, which can form a three-dimensional representation faster than a single orientation view. In this work we present the first experimental multiple orientation muon tomography study. Experimental muon-scatter based tomography was performed using a concrete filled steel drum with several different metal wedges inside, between detector planes. Data was collected from different detector-object orientations by rotating the steel drum. The data collected from each orientation were then combined using two different tomographic methods. Results showed that using a combination of multiple depth-of-field reconstructions, rather than a traditional inverse Radon transform approach used for CT, resulted in more useful images for sparser data. As cosmic ray muon flux imaging is rate limited, the imaging techniques were compared for sparse data. Using the combined depth-of-field reconstruction technique, fewer detector-object orientations were needed to reconstruct images that could be used to differentiate the metal wedge compositions.

Applied Physics (physics.app-ph)↗
DOE OSTI2024

Factorized visual representations in the primate visual system and deep neural networks

Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many different types of information, and optimizing for classification of object identity alone does not constrain how other information may be encoded in visual representations. Information about different scene parameters may be discarded altogether (‘invariance’), represented in non-interfering subspaces of population activity (‘factorization’) or encoded in an entangled fashion. In this work, we provide evidence that factorization is a normative principle of biological visual representations. In the monkey ventral visual hierarchy, we found that factorization of object pose and background information from object identity increased in higher-level regions and strongly contributed to improving object identity decoding performance. We then conducted a large-scale analysis of factorization of individual scene parameters – lighting, background, camera viewpoint, and object pose – in a diverse library of DNN models of the visual system. Models which best matched neural, fMRI, and behavioral data from both monkeys and humans across 12 datasets tended to be those which factorized scene parameters most strongly. Notably, invariance to these parameters was not as consistently associated with matches to neural and behavioral data, suggesting that maintaining non-class information in factorized activity subspaces is often preferred to dropping it altogether. Thus, we propose that factorization of visual scene information is a widely used strategy in brains and DNN models thereof.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Material identification system

A method and apparatus for identifying a material in an object. An image of the object generated from energy passing through the object is obtained by a computer system. The computer system estimates attenuations for pixels in a sensor system from the image of the object to form estimated attenuations. The estimated attenuations represent a loss of the energy that occurs from the energy passing through the object. The computer system also identifies the material in the object using the estimated attenuations and known attenuation information for identifying the material in the object.

Jimenez, Jr., Edward Steven↗
DOE OSTI2023

Model-based image change quantification

A system is provided for identifying and quantizing a change in a scene having objects based on comparison of features representing a target object derived from a first image and a second image that includes the target object. The system segments, based on a scene model of the scene, a second image that includes the target object to identify a second area representing the target object within the second image. The system extracts, from the second image, second features for the target object based on the second area. The system determines a second effectiveness of the second features indicating effectiveness of the second features in representing the target object. The system detects a change based on a difference between first features and the second features factoring in a first effectiveness and the second effectiveness.

Roberts, Randy S.↗
DOE OSTI2020

Update to the Performance Assessment for the Savannah River Site Saltstone Disposal Facility - 20124

In 2019, Savannah River Remediation developed a revision to the performance assessment (PA) on behalf of the U.S. Department of Energy (DOE) Savannah River Operations Office (SR) for the near-surface disposal of low-level waste at the Savannah River Site (SRS) Saltstone Disposal Facility (SDF). Soluble waste from SRS Tank Farms undergoes salt processing to remove cesium and other high activity constituents. The low-activity decontaminated salt solution (DSS) is then immobilized by mixing it into a cementitious waste form known as saltstone. After mixing, the saltstone is poured into leak-tight concrete vaults, known as saltstone disposal units (SDUs), where the waste form cures. By the time of facility closure, the SDF is expected to consist of 15 SDUs with a combined capacity of 1.06 E+09 L (280 Mgal) of cured saltstone. The facility operates under a Disposal Authorization Statement (DAS) from DOE and a permit from the South Carolina Department of Health and Environmental Control (SCDHEC). Since the start of operations in 1990, the SDF has received almost 6.7 E+07 L (18 Mgal) of DSS, resulting in the safe disposal of 2.7 E+16 Bq (7.3 E+05 Ci) of activity. Due to the radioactive decay of short-lived contaminants, the total remaining activity in the disposed waste is estimated to be approximately 1.4 E+16 Bq (3.9 E+05 Ci), as of September 2018. The Disposal Authorization Statement requires a demonstration that the system of engineered and natural features of the disposal facility will limit releases from the facility and be protective of human health and the environment for at least the next 1,000 years. The long-term performance of the facility was evaluated under the requirements of the DoE's Radioactive Waste Management Manual (US DOE Manual 435.1-1). Simulations were performed to demonstrate that the disposal facility would meet performance objectives specified in the manual. The evaluation was based on numerical models that simulate the releases of contaminants from the saltstone waste form. Contaminants were transported through groundwater and air pathways to points of assessment to evaluate compliance. In addition, the potential consequences of an inadvertent human intrusion (IHI) were also evaluated. In accordance with the guidance and recommendations in US DoE's technical standard for DAS, deterministic and probabilistic analyses were performed to demonstrate the SDF system, which includes the engineered cover system, the SDUs, the waste form, and the natural features of the site, provides a reasonable expectation that saltstone disposal will meet performance objectives. Post-closure doses to future members of the public (MOP) were evaluated; dose estimates from the air pathway were well below the 1.0 E-04 Sv/yr (10 mrem/yr) performance objective within 1,000 years, and the calculated doses to the MOP from all exposure pathways, including the groundwater and air pathways, were well below the 2.5 E-04 Sv/yr (25 mrem/yr) performance objective within 1,000 years. Doses following an assumed intrusion event within the facility boundaries were well below the IHI performance objectives, where the acute IHI dose was below the acute IHI dose performance objective of 5.0 E-03 Sv (500 mrem) and the chronic IHI dose was below the chronic IHI dose performance objective of 1.0 E-03 Sv/yr (100 mrem/yr) within 1,000 years. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗