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At least 127 records · Page 7

A Privacy First Path Analysis using Clickstream Data

In the modern digital economy, data-driven decision making is crucial for effectively meeting the ever-evolving demands of consumer engagement and satisfaction. Clickstream data has become invaluable for understanding customer behavior, yet concerns over privacy and security persist, especially with some internet service providers profiting from its sale. This article introduces an innovative methodology that blends experiential learning with advanced cryptographic techniques, including differential privacy and graph analytics. The core objective of this methodology is to estimate Customer Lifetime Value (CLV) by analyzing clickstream data, achieving an average prediction accuracy of 92.4% in user engagement levels while ensuring user anonymity through Recency, Frequency, and Monetary (RFM) analysis. Our study introduces the concept of a “data depositor” and a privacy manager, employing the composition theorem to merge non-adaptive queries effectively. Privacy budgets (? = 1.0, d = 10-5), sensitivity-specific techniques, and data partitioning were applied. Randomization and noise addition protect data integrity, with special handling for categorical values. This approach, differing from prior studies, offers a 12.6% improvement in privacy-preserving targeting accuracy while maintaining strict confidentiality, presenting a novel path forward in data-driven decision-making.

Frequency and Monetary (RFM) analysis↗

Charged Current Coherent Pion Production Cross-Section Measurement at MicroBooNE

Coherent pion production, characterized by a neutrino interacting with an entire nucleus without breaking it apart, results in a forward-going muon, pion, and a low-momentum recoil nucleus. By leveraging an improved understanding of particle identification and background parameterization, we aim to achieve a new level of sensitivity to coherent interactions at low neutrino energy. The outcome of this analysis will contribute to ongoing efforts to model neutrino nucleus interactions accurately in neutrino oscillation studies and beyond Standard Model searches in MicroBooNE and future experiments, such as DUNE. We present progress towards a measurement of charged current coherent pion production cross-section on argon with the MicroBooNE liquid argon time projection chamber detector. This measurement will use MicroBooNE's full dataset collected from the Booster Neutrino Beam with a total exposure of \( 1.3 \times 10^{21} \) protons-on-target and average neutrino energy of 0.8 GeV.

Hussain, Adil [Kansas State U.]↗

Development of a structural optimization capability for the aeroelastic tailoring of composite rotor blades with straight and swept tips

This paper describes the development of a new structural optimization capability aimed at the aeroelastic tailoring of composite rotor blades with straight and swept tips. The primary objective is to reduce vibration levels in forward flight without diminishing the aeroelastic stability margins of the blade. In the course of this research activity a number of complicated tasks have been addressed: (1) development of a new, aeroelastic stability and response analysis; (2) formulation of a new comprehensive sensitive analysis, which facilitates the generation of the appropriate approximations for the objective and the constraints; (3) physical understanding of the new model and, in particular, determination of its potential for aeroelastic tailoring, and (4) combination of the newly developed analysis capability, the sensitivity derivatives and the optimizer into a comprehensive optimization capability. The first three tasks have been completed and the fourth task is in progress.

Friedmann, P. P.↗

A Comparison of Three Algorithms for Orion Drogue Parachute Release

The Orion Multi-Purpose Crew Vehicle is susceptible to ipping apex forward between drogue parachute release and main parachute in ation. A smart drogue release algorithm is required to select a drogue release condition that will not result in an apex forward main parachute deployment. The baseline algorithm is simple and elegant, but does not perform as well as desired in drogue failure cases. A simple modi cation to the baseline algorithm can improve performance, but can also sometimes fail to identify a good release condition. A new algorithm employing simpli ed rotational dynamics and a numeric predictor to minimize a rotational energy metric is proposed. A Monte Carlo analysis of a drogue failure scenario is used to compare the performance of the algorithms. The numeric predictor prevents more of the cases from ipping apex forward, and also results in an improvement in the capsule attitude at main bag extraction. The sensitivity of the numeric predictor to aerodynamic dispersions, errors in the navigated state, and execution rate is investigated, showing little degradation in performance.

Matz, Daniel A.↗

Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence.

Efficiently performing predictive studies of irradiated particle-laden turbulent flows has the potential of providing significant contributions towards better understanding and optimizing, for example, concentrated solar power systems. As there are many uncertainties inherent in such flows, conducting uncertainty quantification analyses is fundamental to improve the predictive capabilities of the numerical simulations. For largescale, multi-physics problems exhibiting high-dimensional uncertainty, characterizing the stochastic solution presents a significant computational challenge as many methods require a large number of high-fidelity, forward model solves. This requirement results in the need for a possibly infeasible number of simulations when a typical converged high-fidelity simulation requires intensive computational resources. To reduce the cost of quantifying high-dimensional uncertainties, we investigate the application of a non-intrusive, bi-fidelity approximation to estimate statistics of quantities of interest associated with an irradiated particle-laden turbulent flow. This method relies on exploiting the low-rank structure of the solution to accelerate the stochastic sampling and approximation processes by means of cheaper-to-run, lower fidelity representations. The application of this bi-fidelity approximation results in accurate estimates of the QoI statistics while requiring a small number of high-fidelity model evaluations. It also enables efficient computation of sensitivity analyses which highlight that epistemic uncertainty plays an important role in the solution of irradiated, particle-laden turbulent flow.

42 ENGINEERING↗

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

We report iTOUGH2 is a simulation-optimization framework for the TOUGH suite of nonisothermal multiphase flow models and related simulators of geophysical, geochemical, and geomechanical processes. After appropriate parameterization of subsurface structures and their properties, iTOUGH2 runs simulations for multiple parameter sets and analyzes the resulting output for parameter estimation through automatic model calibration, local and global sensitivity analyses, data-worth analyses, and uncertainty propagation analyses. Development of iTOUGH2 is driven by scientific challenges and user needs, with new capabilities continually added to both the forward simulator and the optimization framework. This paper provides a summary description of methods and features implemented in iTOUGH2, and discusses the usefulness and limitations of an integrated simulation-optimization workflow in support of the characterization and analysis of complex multiphysics subsurface systems.

58 GEOSCIENCES↗

Using probabilistic analysis to assess the reliability of predicted SRB aft-skirt stresses

Probabilistic failure analysis is a tool to predict the reliability of a part or system. Probabalistic techniques were used to predict critical stresses which occur in the solid rocket booster aft-skirt during main engine buildup, immediately prior to lift-off. More than any other hold down post (HDP) load component, the Z loads are sensitive to variations in strains and calibration constants. Also, predicted aft-skirt stresses are strongly affected by HDP load variations. Therefore, the instrumented HDP are not effective load transducers for Z loads, and, when used with aft skirt stress indicator equations, yield estimates with large uncertainty. Monte Carlo simulation proved to be a straight forward way of studying the overlapping effects of multiple parameters on predicted equipment performance. An advantage of probabilistic analysis is the degree of uncertainty of each parameter as stated explicitly by its probability distribution. It was noted, however, that the choice of parameter distribution had a large effect on the simulation results. Many times these distributions must be assumed. The engineer who is designing the part should be responsible for the choice of parameter distribution.

Richardson, James A.↗

Tomographic analysis of neutron and gamma pulse shape distributions from liquid scintillation detectors at Joint European Torus

The Joint European Torus (JET, Culham, UK) is the largest tokamak in the world devoted to nuclear fusion experiments of magnetic confined Deuterium (D)/Deuterium-Tritium (DT) plasmas. Neutrons produced in these plasmas are measured using various types of neutron detectors and spectrometers. Two of these instruments on JET make use of organic liquid scintillator detectors. The neutron emission profile monitor implements 19 liquid scintillation counters to detect the 2.45 MeV neutron emission from D plasmas. A new compact neutron spectrometer is operational at JET since 2010 to measure the neutron energy spectra from both D and DT plasmas. Liquid scintillation detectors are sensitive to both neutron and gamma radiation but give light responses of different decay time such that pulse shape discrimination techniques can be applied to identify the neutron contribution of interest from the data. The most common technique consists of integrating the radiation pulse shapes within different ranges of their rising and/or trailing edges. In this article, a step forward in this type of analysis is presented. The method applies a tomographic analysis of the 3-dimensional neutron and gamma pulse shape and pulse height distribution data obtained from liquid scintillation detectors such that n/γ discrimination can be improved to lower energies and additional information can be gained on neutron contributions to the gamma events and vice versa.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Preface to the Special Issue on TOUGH Symposium 2015

The TOUGH Symposium 2015 was held in Berkeley, California, September 28-30, 2015. The TOUGH family of codes, developed at the Energy Geosciences Division of Lawrence Berkeley National Laboratory (LBNL), is a suite of computer programs for the simulation of multiphase and multicomponent fluid and heat flows in porous and fractured media with applications in many geosciences fields, such as geothermal reservoir engineering, nuclear waste disposal, geological carbon sequestration, oil and gas reservoirs, gas hydrate research, vadose zone hydrology and environmental remediation. Since the first release in the 1980s, many modifications and enhancements have been continuously made to TOUGH and its various descendants (iTOUGH2, TOUGH+, TOUGH-MP, TOUGHREACT, TOUGH+HYDRATE, TMVOC...), at LBNL and elsewhere. Today, these codes are used worldwide in academia, government organizations and private companies in problems involving coupled hydrological, thermal, biogeochemical and geomechanical processes. The Symposia, organized every 2-3 years, bring together developers and users for an open exchange on recent code enhancements and applications. In 2015, the Symposium was attended by one hundred participants, representing thirty-four nationalities. This Special Issue in Computers & Geosciences gathers extended versions of selected Symposium proceedings related to (i) recent enhancements to the TOUGH family of codes and (ii) coupled flow and geomechanics processes modeling. In this special issue, a paper by Jung et al. provides a new base version of TOUGH, TOUGH3. This latest version addresses the computational robustness and efficiency needed for the increasing complexity of the simulated processes and the growing size of model domains. Moreover, it consolidates the serial and parallel versions into a single code, hence, inconsistencies between different versions are less likely to occur, and code maintenance and development become more efficient. Finsterle et al. present a review of the capabilities of iTOUGH2 and illustrate the workflow of an integrated simulation-optimization framework. Liu et al. present an approach to reduce the computational cost of performing Bayesian inverse modeling and demonstrate their approach using a synthetic experiment simulated with TOUGH2. Regarding the mesh generation process, the paper by Doughty presents a generalization of the grid-generation algorithm embedded in TOUGH2 (MESHMAKER) to create one-column grids with fractal dimension, useful for representing flow through fractures or highly heterogeneous media with fractal geometry, and also for inverse methods. Sentís and Gable present a module to interface the open source code Lagrit with TOUGH2, that assists in the processes of mesh generation and model setup, and that can be particularly useful for complex geometries and large models. Bonduà et al. present a pre-processing tool (VORO2MESH) that features a full 3D Voronoi approach for structured and unstructured grids, and an enhanced post-processor (TOUGH2Viewer) for the visualization of 3D Voronoi grids. The literature review shows that coupled fluid flow and geomechanics has gained increasing attention in the last years in many geosciences fields. In this context, several codes of the TOUGH family have been successfully coupled with geomechanics software. The paper by Rutqvist presents a review of some of these TOUGH-based geomechanics models, of which the TOUGH-FLAC simulator – presented for the first time in the TOUGH Symposium 2003 – is well-known worldwide and has been used in a large variety of applications, encompassing the application domains of the TOUGH codes. Blanco-Martín et al. present an extension of TOUGH-FLAC to the finite strain framework, motivated by the existence of large strains associated with rock salt deformation in the context of heat-generating nuclear waste disposal. Following a paper published in the Special Issue of the TOUGH Symposium 2012 in this journal, Kim et al. present the current status of the TOUGH-RSBN simulator for coupled hydro-mechanical modeling of hydraulic fracturing using a discrete fracture network approach, and present some validation and demonstration cases. Rinaldi and Nespoli present TOUGH-SEED, an injection-induced seismicity modeling approach using TOUGH2 and a geomechanics stochastic model, and apply it to the Basel EGS project. Finally, Rinaldi et al. use the PEST protocol implemented in iTOUGH2, combined with TOUGH-FLAC as the forward model, to perform inverse modeling for the In Salah CO2 demonstration site in Algeria. Using pore pressures and InSAR displacements as observations, this approach allows for a multi-physics joint inversion and takes advantage of the inverse capabilities of iTOUGH2 (parameter estimation, sensitivity analysis, uncertainty estimation …), applied to coupled fluid flow and geomechanics. On behalf of the members of the TOUGH Symposium 2015 Organizing Committee, I hope that this collection of papers will provide the readers of Computers & Geosciences with a recent view of the capabilities of the TOUGH family of codes, as well as with current modeling research domains in the geosciences. Last but not least, I would like to express my gratitude to all the reviewers who kindly contributed to this Special Issue, as well as the Journal staff who have made this publication possible.

99 GENERAL AND MISCELLANEOUS↗

Ground-Based Remote Retrievals of Cumulus Entrainment Rates

While fractional entrainment rates for cumulus clouds have typically been derived from airborne observations, this limits the size and scope of available data sets. To increase the number of continental cumulus entrainment rate observations available for study, an algorithm for retrieving them from ground-based remote sensing observations has been developed. This algorithm, called the Entrainment Rate In Cumulus Algorithm (ERICA), uses the suite of instruments at the Southern Great Plains (SGP) site of the United States Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility as inputs into a Gauss-Newton optimal estimation scheme, in which an assumed guess of the entrainment rate is iteratively adjusted through intercomparison of modeled liquid water path and cloud droplet effective radius to their observed counterparts. The forward model in this algorithm is the Explicit Mixing Parcel Model (EMPM), a cloud parcel model that treats entrainment as a series of discrete entrainment events. A quantified value for measurement uncertainty is also returned as part of the retrieval. Sensitivity testing and information content analysis demonstrate the robust nature of this method for retrieving accurate observations of the entrainment rate without the drawbacks of airborne sampling. Results from a test of ERICA on three months of shallow cumulus cloud events show significant variability of the entrainment rate of clouds in a single day and from one day to the next. The mean value of 1.06 km-¹ for the entrainment rate in this dataset corresponds well with prior observations and simulations of the entrainment rate in cumulus clouds.

Wagner, Timothy J.↗

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

Abstract. Land models are essential tools for understanding and predicting terrestrial processes and climate–carbon feedbacks in the Earth system, but uncertainties in their future projections are poorly understood. Improvements in physical process realism and the representation of human influence arguably make models more comparable to reality but also increase the degrees of freedom in model configuration, leading to increased parametric uncertainty in projections. In this work we design and implement a machine learning approach to globally calibrate a subset of the parameters of the Community Land Model, version 5 (CLM5) to observations of carbon and water fluxes. We focus on parameters controlling biophysical features such as surface energy balance, hydrology, and carbon uptake. We first use parameter sensitivity simulations and a combination of objective metrics including ranked global mean sensitivity to multiple output variables and non-overlapping spatial pattern responses between parameters to narrow the parameter space and determine a subset of important CLM5 biophysical parameters for further analysis. Using a perturbed parameter ensemble, we then train a series of artificial feed-forward neural networks to emulate CLM5 output given parameter values as input. We use annual mean globally aggregated spatial variability in carbon and water fluxes as our emulation and calibration targets. Validation and out-of-sample tests are used to assess the predictive skill of the networks, and we utilize permutation feature importance and partial dependence methods to better interpret the results. The trained networks are then used to estimate global optimal parameter values with greater computational efficiency than achieved by hand tuning efforts and increased spatial scale relative to previous studies optimizing at a single site. By developing this methodology, our framework can help quantify the contribution of parameter uncertainty to overall uncertainty in land model projections.

54 ENVIRONMENTAL SCIENCES↗

Constraining neutrinophilic mediators at FASER ν , FLArE, and FASER ν 2

High energy collider neutrinos have been observed for the first time by the FASER ν experiment. The detected spectrum of collider neutrinos scattering off nucleons can be used to probe neutrinophilic mediators with GeV-scale masses. We find that constraints on the pseudoscalar (axial vector) neutrinophilic mediator are close to the scalar (vector) case since they have similar cross section in the neutrino massless limit. We perform an analysis on the measured muon spectra at FASER ν , and find that the bounds on the vector mediator from the current FASER ν data are comparable to the existing bounds at m Z ′ ≈ 0.2 GeV . We also study the sensitivities to a neutrinophilic mediator at future Forward Physics Facilities including FLArE and FASER ν 2 by using both the missing transverse momentum and the charge identification information. We find that FLArE and FASER ν 2 can impose stronger bounds on both the scalar and vector neutrinophilic mediators than the existing bounds. The constraints on the scalar mediator can reach 0.08 (0.1) for m ϕ ≲ 1 GeV with (without) muon charge identification at FASER ν 2 . Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hypercomplex Automatic Differentiation in the Eulerian Hydrocode PAGOSA

Enabling the computation of partial derivatives or sensitivities in production hydrocodes is beneficial for design, optimization, sensitivity analysis, and uncertainty quantification. Traditional finite difference approximations of these sensitivities are inefficient since convergence studies of the step size is required for each parameter of interest. For these reasons, HYPercomplex Automatic Differentiation (HYPAD) was implemented in the Eulerian hydrocode PAGOSA. HYPAD is analogous to forward-mode automatic differentiation except hypercomplex numbers (numbers with multiple imaginary parts) are used instead of dual numbers. Accurate partial derivatives can be computed of all state variables with respect to multiple input variables in a single run. The method was implemented using operator overloading to handle hypercomplex algebra. HYPAD was demonstrated and verified on Sod’s shock tube problem to compute derivatives of the state variables with respect to a material parameter, initial conditions, and geometry.

97 MATHEMATICS AND COMPUTING↗

Topics in the optimization of millimeter-wave mixers

This report is in three parts: 1. In the first part a user-oriented computer program for the analysis of single-ended Schottky diode mixers is described. The program is used to compute the performance of a 140-220 GHz mixer and excellent agreement with measurements at 150 and 180 GHz is obtained. A sensitivity analysis indicates the importance of various diode and mount characteristics on the mixer performance. 2. The second part of this report describes a computer program for the analysis of varactor diode multipliers. The diode may operate in either the reverse biased varactor mode or with substantial forward current flow where the conversion mechanism is predominantly resistive. In addition, a design for a varactor diode doubler, tunable over an output frequency range of 150-220 GHz, is given. The doubler has 10-20% conversion efficiency with an instantaneous bandwidth of 3%. 3. The third section of this report contains a description and analysis of i new H-plane rectangular waveguide transformer. The transformer can be made luckily and easily in split-block waveguide using a standard slitting saw. It is particularly suited for use in the millimeter-wave band, replacing conventional electroformed stepped transformers. A theoretical analysis of the transformer is given, and good agreement is obtained with measurements made at X-band. Design curves are included for transitions which have a VSWR <1.2 over a full waveguide band when the impedance ratio is as high as 4 to 1.

Millimeter-wave↗

Bayesian characterization and forward propagation of the uncertainty in thermodynamic models for redox active materials

Demonstrating the thermodynamic efficiency of hydrogen conversion processes using various materials is a critical step in developing new technologies for storing concentrated solar energy, and is largely accomplished by using a thermodynamic model derived from experimental data. A main goal of this project is to calculate the uncertainty of the thermodynamic efficiency by calculating the uncertainty of the components that feed into the efficiency. Many different models and data sets were used to test the workflow. First, the models were fit to the data using a Bayesian Inference and a method called Markov Chain Monte Carlo (MCMC), which found the maximum a priori parameters, and a posterior probability distribution of the parameters. Next, the different models were compared to each other using model evidence values. It was found that for cleaner data sets, overfitting had not yet been reached, and the most complicated model was ideal, but on the noisier data sets, the less complex models were favored because the more complicated models resulted in overfitting. Next, forward propagation was used to calculate the enthalpy change and its associated uncertainty. A few variations on the models were tried, such as fitting in a different variable, producing negligible or negative effects on the fits of the models. Thus, the original models were used. A sensitivity analysis was performed, and used to calculate the model error. On the cleaner data sets, there was very minimal experimental noise, and thus, all resulting error was from the model. With consideration of the model error, the models fit the data very well, and the simpler model had a high model error, as expected. All these components will then be used to calculate the thermodynamic efficiency of the different materials.

14 SOLAR ENERGY↗

A Novel Dew Point Meter: Application to the Measurement of the Sulfuric Acid Dew Point for Combustion Flue Gas

Accurate knowledge of acid dew point is essential for industrial and applied combustion applications. Sulfur in the fuel or raw materials is converted to sulfur dioxide (SO2) during combustion, and a portion of the SO2 is oxidized to sulfur trioxide (SO3). The SO3 will react to form H2SO4 vapor when in the presence of water vapor. Even with just trace levels of H2SO4 vapor in the gas phase (1-10 ppm), the dew point can reach 100°C and higher. To avoid acid condensation and the resulting corrosion on heat recovery equipment, plant engineers must ensure that surface temperatures are above the acid dew point, but this decreases the efficiency of thermal energy recovery. Thus, there is a trade-off between minimizing equipment corrosion and maximizing thermal energy recovery, and the acid dew point is a key parameter for this optimization. Commercially available acid dew point meters use electric conductivity sensors. These sensors are known to greatly underestimate the dew point due to their low sensitivity. In addition, no validation testing has been reported for these units and they are often expensive. In this work, we analyze the theory of the sulfuric acid condensation and develop a novel dew point meter based on this analysis. The meter consists of a novel optical instrument that is designed to monitor the slightest appearance of condensation on a hydrophobic window surface as the surface temperature of the window is slowly decreased. In this way, an accurate measurement of the dew point is obtained under a wide range of concentrations. The basis of the instrument is that a collimated beam from a diode laser will generate forward scattered light when the beam encounters surface condensate, and a sophisticated array detector is used to sensitively monitor the onset of light scattering. The measurement procedures are established to rapidly find the acid dew point, while minimizing error. Further, to calibrate the dew point meter we developed a calibration system based on a liquid bubbler that can generate a stable gas flow with a known sulfuric acid dew point. Test results show that the dew point meter can accurately measure acid dew point over a wide range. For H2SO4 vapor concentrations as low as 6 ppm the acid dew point is measured with an error of only ~1°C. To demonstrate the versatility of this instrument, the dew point meter was adapted for use with a high-pressure flow cell to allow for measurements of the dew point of flue gas from pressurized oxy-fuel combustion in a 100 kWth pressurized reactor.

Cheng, Mao↗

Characteristics and selection of near-fault simulated earthquake ground motions for nonlinear analysis of buildings

Earthquake-induced ground shaking near rupturing faults is highly sensitive to the rupture characteristics, seismic wave propagation patterns and site conditions, and field recordings of near-fault shaking are relatively sparse. These challenges complicate the assessment of the seismic performance of near-fault structures. A common approach to representing near-fault ground motion in engineering analysis is to explicitly consider and select records with strong directivity pulses (pulse records). We use three-dimensional high-resolution physics-based earthquake simulations to test this approach in the context of scenario-based ground motion record selection, and to study the important characteristics of near-fault ground shaking. We highlight the deficiencies associated with classifying near-fault simulated records as “pulse” or “non-pulse,” based on the presence of a single dominating pulse in the velocity time history. We show that this approach is inadequate for characterizing near-fault shaking on soft soils which can be dominated by both forward rupture directivity and basin amplification effects. We conduct ground motion selection experiments for the analysis of near-fault structures with and without explicit classification of the pulse features in the records, and evaluate the bias in the predicted structural demands. We find that the maximum interstory drift demands on building structures imposed by unscaled site-specific simulated ground motion records selected based on relevant spectral shape features are not sensitive to the classification of records as pulse/non-pulse. Therefore, with regard to predicting the maximum interstory drifts in near-fault buildings, we do not find justification for the binary pulse classification of near-fault records.

42 ENGINEERING↗

Building a Credible and Updated WIPP Performance Assessment - New Knowledge Versus Conservative Assumptions and FEP Analysis, A Balancing Act - 16299

Conservative assumptions are important components in conceptual model development where limited data is available. And, as appropriate, during the early 1990's Department of Energy (DOE) adopted many conservative assumptions in the development of the Waste Isolation Pilot Plant's (WIPP's) 24 Conceptual Models incorporated in DOE's 1996 Compliance Certification Application (CCA) performance assessment (PA). Many of these assumptions were formulated and documented in the WIPP relevant features, events and processes (FEPs) analyses; others were adopted when developing input parameter values and their distributions that were used as inputs to computer models. The Agency accepted these conservative assumptions during their 1996 CCA assessment for several reasons; 1) at the time there was a scarcity of data related to long-term behavior of many parameters needed to be incorporated in the PA, 2) sensitivity studies performed during this time period determined that the affected 'conservative' assumptions adopted for some parameters had minimal to no impact on repository performance; and, 3) DOE could demonstrate compliance with EPA's radioactive waste disposal regulations while adopting conservative assumptions and data. Since the initial 1996 CCA DOE has modified the repository panel closure design, and the repository footprint in the experimental areas has expanded. These modifications were incorporated into DOE's 2014 Compliance Re-certification Application for WIPP. Additionally, there have been numerous investigations related to both the short- and long-term behavior of salt in a repository setting. As a result, the Agency is reassessing the use of these conservative assumptions and the continued applicability of the original FEP analyses, primarily developed during DOE's 1996 PA and carried forward to the current re-certification. This paper examines some of these analyses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗