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At least 163 records · Page 9

Simulation-based Performance Evaluation of Model Predictive Control for Building Energy Systems

The performance of model predictive control (MPC) can be significantly affected by different choices of controller parameters such as the time intervals for model discretization and control sampling. Due to the lack of a systematic understanding on how these parameters affect control performance, they are usually selected arbitrarily in practice.In this paper, the combined impacts of selected time intervals for model discretization and control sampling on the performance of MPC are comprehensively investigated for the first time through detailed simulations. Specifically, a typical MPC strategy is first designed to improve building operations based on a reduced-order model of building dynamics. Then, the performance of the designed MPC is evaluated against different choices of time intervals for model discretization and control sampling on a simulated office building. The detailed simulation results reveal that the time interval for model discretization has a much greater influence on the performance of MPC than the time interval for control sampling. Although the time interval for control sampling usually receives more attentions in practice, it turns out that the time interval for model discretization affects the prediction performance, cost saving, and computation time simultaneously and more significantly. Therefore, the simulation-based performance evaluation presented here sheds light on the impacts of different time intervals and facilitates their selection for practical applications of MPC to building operations

Huang, Sen↗

FY2021 Improvements to the New CTH Code Verification & Validation Test Suite

Over the past few years, the CTH multiphysics hydrocode has overhauled its software quality and testing processes, implementing current best practices in software quality and building a robust V&V test suite comprised of traditional hydrocode verification problems, including ASC Tri-Lab Test Suite and Enhanced Tri-Lab Test Suite problems, as well as validation problems for some of CTH’s most frequently used equations of state, materials models, and other key capabilities. Substantial progress towards building this new test suite was made in FY19 and FY20. In FY21, the test suite has been expanded to include verification and validation tests of the Steinberg-Guinan-Lund (ST) viscoplastic model and the Johnson Cook (JFRAC) fracture model. Additionally, two new verification tests were added, covering hydrodynamics and high explosive (HE) modeling capabilities: the Kidder Gaussian density problem and the Escape of HE Products (EHEP) problem from the Tri-Lab Test Suite. This report discusses each of these test problems in detail. Verification test results are compared to analytic solutions. Validation test results are compared to experimental data. Wherever possible, convergence or mesh refinement studies are included. Additionally, while implementing the Kidder verification problem, a bug was identified that affects the use of tables to initialize pressure or density in 1D or 2D calculations. A brief discussion of the bug and its fix is included. CTH demonstrates good performance overall on the new test suite problems. Simulation results showed good agreement with analytic solutions for the Kidder problem, with convergence rates ranging between 1.8 and sub-linear, and relatively good agreement for the EHEP problem, though convergence rates for pressure and density were nearly 0. The ST and JFRAC strain rate loading verification tests show good agreement with analytic solutions. Likewise, CTH simulation results show good agreement with experimental validation data, including Taylor rod impact testing, for the materials tested. Future V&V work will focus on adding 2D and 3D versions of existing verification tests as well as adding validation tests of other frequently used capabilities such as other fracture models.

42 ENGINEERING↗

Development and Validation of SAM Multi-dimensional Flow Model for Thermal Mixing and Stratification Modeling

Thermal mixing and stratification in large pools or enclosures are very important phenomena that are critical to nuclear reactor safety. Because of the wide ranges of time and length scales associated with such phenomena, accurate modeling and simulation of thermal mixing and stratification remain as the key unresolved, challenging problems for reactor transient analyses. In traditional system analysis codes, simplified zero-dimensional (0-D) models are widely used for their high numerical efficiency, but they generally suffer from very limited prediction accuracies or range of applicability. Like traditional system analysis codes, the current version of the SAM code has implemented such simplified 0-D and one-dimensional mixing models. On the other hand, high-resolution Computational Fluid Dynamics (CFD) tools are often used to model complex thermal mixing and stratification phenomena. They are, however, generally numerically expensive, and they require large amounts of computational resources. It is therefore desirable to implement advanced and efficient thermal mixing and stratification modeling capabilities embedded in a system analysis code. This approach will improve the accuracy of reactor safety analyses when thermal mixing and stratification are involved, and also avoid using the large computational resources needed for high-resolution CFD analysis. Currently, with the support of the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation program, an effort has been launched to develop and implement a multi-dimensional flow model in the system analysis code SAM, and demonstrate its applications to model thermal mixing and stratification phenomena in large enclosures. The main outcomes of this research and development activity are summarized in this report, which presents an attempt to include a built-in advanced multi-dimensional flow model in a system analysis code with the focus on overcoming the simulation challenges of thermal mixing and stratification phenomena. In this report, we start with the introduction of existing SAM code capabilities to simulate thermal mixing and stratification phenomena, which is followed by a short summary of the multi-dimensional model implemented in the SAM code, including both the physical model and the Finite Element Method code implementation. In this study, two options were implemented in the SAM code to model turbulent flows: a relatively simple built-in turbulence model and an interface to accept externally computed turbulent viscosities (e.g., from a high- resolution CFD simulation). Code validation studies on this newly added capability were then carried out to compare SAM simulation results with experimental data from the SUPERCAVNA facility, which was designed to study the complex flow recirculation and thermal stratification phenomena relevant to sodium fast reactor designs. In this study, one transient and two steady-state test cases were used for code validation. Different approaches have been used to model the complex turbulence flow fields in the SUPERCAVNA facility. A highly simplified zero-equation turbulence model was first used, but it was determined that it is too simple to capture the complex turbulence flow fields in these test cases. Subsequently, the code validation continued with the use of turbulent viscosity data from high-resolution STAR-CCM+ CFD simulations to improve the accuracy of the results. Using this approach, the SAM simulation results showed very good agreement with both the SUPERCAVNA experimental data and STAR-CCM+ simulation results. In this report, we demonstrate the development, implementation, and successful validation of a multi-dimensional flow model in the SAM code, which aims to improve the simulation accuracy for complex thermal mixing and stratification phenomena. Lessons have also been learned, including that in cases where the flow fields are not well predicted by the zero-equation model, the iinput of turbulent viscosities from an external source can enhance the overall predictive capabilities needed to accurately capture complex thermal-hydraulic phenomena. Therefore, future research will be needed to further improve the code’s capabilities, such as by developing a more efficient and robust approach to capture the turbulence effects in the SAM code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Legacy Well Leakage Risk Analysis at the Farnsworth Unit Site

This paper summarizes the results of the risk analysis and characterization of the CO 2 and brine leakage potential of Farnsworth Unit (FWU) site wells. The study is part of the U.S. DOE’s National Risk Assessment Partnership (NRAP) program, which aims to quantitatively evaluate long-term environmental risks under conditions of significant geologic uncertainty and variability. To achieve this, NRAP utilizes risk assessment and computational tools specifically designed to quantify uncertainties and calculate the risk associated with geologic carbon dioxide (CO 2 ) sequestration. For this study, we have developed a workflow that utilizes physics-based reservoir simulation results as input to perform leakage calculations using NRAP Tools, specifically NRAP-IAM-CS and RROM-Gen. These tools enable us to conduct leakage risk analysis based on ECLIPSE reservoir simulation results and to characterize wellbore leakage at the Farnsworth Unit Site. We analyze the risk of leakage from both individual wells and the entire field under various wellbore integrity distribution scenarios. The results of the risk analysis for the leakage potential of FWU wells indicate that, when compared to the total amount of CO 2 injected, the highest cemented well integrity distribution scenario (FutureGen high flow rate) exhibits approximately 0.01% cumulative CO 2 leakage for a 25-year CO 2 injection duration at the end of a 50-year post-injection monitoring period. In contrast, the highest possible leakage scenario (open well) shows approximately 0.1% cumulative CO 2 leakage over the same time frame.

54 ENVIRONMENTAL SCIENCES↗

Phase-field modeling of crack growth and mitigation in solid oxide cells

Fracture and crack growth is one of the main degradation mechanisms in solid oxide cells (SOCs). However, the modeling of crack growth in SOCs is challenging due to their complex microstructures and possible plasticity development within the Ni particles in Ni-based SOC electrodes. In this study, a phase-field fracture model is developed, which incorporates the SOC microstructures and phase-dependent material properties, including yield strength, fracture toughness in the bulk and at the interphase boundaries. The model is employed to study crack initiation and growth under thermal and redox cycling on the hydrogen electrode side of SOCs. The simulation results demonstrate that under thermal cycling, work-zone cracking dominates in electrolyte-supported SOCs with cracks initiated at the triple-phase boundaries, while only minor mechanical degradation occurs in hydrogen-electrode-supported SOCs after hundreds of thermal cycles. Under redox cycling, through-cracking of yttria-stabilized zirconia (YSZ) in the hydrogen electrode and electrolyte layers dominates. Finally, the simulation results suggest several crack-mitigation strategies, including decreasing the porosity in the hydrogen electrode support layer and synchronizing thermal strain to balance oxidation strain.

08 HYDROGEN↗

Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification

Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs) at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the Meta-Alert System (MAS), developed by Electrical Grid Monitoring, Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases, distribution system state estimation (DSSE) and fault identification are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute J1 feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.

distribution system↗

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

Comparing Retrofit Wall Performance Predicted from Hygrothermal Simulations to Measurements

Over the past few years ORNL has been showing that WUFI® can be used to predict the moisture performance of walls when exposed to diffusion of water vapor, convection of moist air through the wall, and solar driven moisture. This is accomplished by comparing the hygrothermal simulation results to carefully instruments walls exposed to these phenomena in a climate chamber. In FY 2018, three stick-built walls were succumbed to typical Chicago, Illinois weather conditions in Oak Ridge National Laboratory’s Heat, Air and Moisture chamber. The measured temperature, relative humidity, and moisture content within these walls were compared with WUFI hygrothermal simulation results. In FY 2019, similar experiments and comparisons with WUFI results were completed with two walls, a structural insulated panel-based wall and a concrete masonry unit-based wall. In FY 2020, experiments were completed for a probable exterior retrofit of a wall which included adding cavity and continuous insulation. Two pairs of walls were tested by exposing them to Chicago winter weather with a positive pressure pushing outside air into the wall. The results from the FY 2020 experiments are reported here.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Gravitational waves from global cosmic strings and cosmic archaeology

Global cosmic strings are predicted in many motivated extensions to the Standard Model of particle physics, with close connections to axion dark matter physics. Recent studies suggest that, although subdominant relative to Goldstone emission, gravitational wave (GW) signals from global strings can be detectable with current and planned GW detectors such as LIGO, LISA, DECIGO/BBO, ET/CE and AEDGE/AION, as well as pulsar timing arrays such as PPTA, NANOGrav and SKA. This work is an extensive, updated study on GWs from a global cosmic string network, taking into account of the most recent developments related to the subject. The main analysis is based on the analytical Velocity-dependent One-Scale (VOS) model calibrated with recent simulation results, which provides a generic protocol for such calculations with details given. We also demonstrate how the GW signal can be influenced with variations to the baseline model: this includes considering the uncertainties of model parameters and the potential deviation from the conventional VOS model prediction (i.e. the scaling behavior) as suggested by some of the recent simulation results. Furthermore, we investigated in detail the effect of a non-standard cosmology (e.g. early matter domination or kination) or new particle species on the GW signals from global strings. We demonstrate that the frequency spectrum of GW background from global cosmic strings can be used to probe the cosmic history prior to the Big Bang nucleosynthesis (BBN) (i.e. the primordial dark age) up to a temperature of T ~ 10 8 GeV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Verification of Coupled Hydraulic Fracturing Simulators Using Laboratory-Scale Experiments

In this work, we aim to verify the predictions of the numerical simulators, which are used for designing field-scale hydraulic stimulation experiments. Although a strong theoretical understanding of this process has been gained over the past few decades, numerical predictions of fracture propagation in low-permeability rocks still remains a challenge. Against this background, we performed controlled laboratory-scale hydraulic fracturing experiments in granite samples, which not only provides high-quality experimental data but also a well-characterized experimental set-up. Using the experimental pressure responses and the final fracture sizes as benchmark, we compared the numerical predictions of two coupled hydraulic fracturing simulators—CSMP and GEOS. Both the simulators reproduced the experimental pressure behavior by implementing the physics of Linear Elastic Fracture Mechanics (LEFM) and lubrication theory within a reasonable degree of accuracy. The simulation results indicate that even in the very low-porosity (1–2 %) and low-permeability (10 -18 m 2 - 10 -19 m 2 ) crystalline rocks, which are usually the target of EGS, fluid-loss into the matrix and unsaturated flow impacts the formation breakdown pressure and the post-breakdown pressure trends. Therefore, underestimation of such parameters in numerical modeling can lead to significant underestimation of breakdown pressure. The simulation results also indicate the importance of implementing wellbore solvers for considering the effect of system compressibility and pressure drop due to friction in the injection line. The varying injection rate as a result of decompression at the instant of fracture initiation affects the fracture size, while the entry friction at the connection between the well and the initial notch may cause an increase in the measured breakdown pressure.

15 GEOTHERMAL ENERGY↗

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using row-resolution (i.e., 15 minutes) smart meter data. We first demonstrate that the electricity consumption profiles on mild-temperature days can be used to approximate the base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed from the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and verify the proposed methods. Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers.

Kim, Hyeonjin↗

Numerical error analysis of SOLPS-ITER simulations of EAST

Abstract Plasma edge simulations with codes like SOLPS-ITER are widely employed to interpret fusion experiments. However, numerical errors appearing in such simulations are rarely investigated, despite their potential large impact on simulation results. These errors consist of the statistical error and the bias, both resulting from the finite number of employed EIRENE Monte Carlo particles and incomplete convergence, and the discretization error due to the finite resolution of the computational grids. In this contribution, the resulting numerical errors on simulations of pure deuterium and neon seeded H-mode EAST discharges are examined. The statistical error can be kept small compared to other numerical error contributions by averaging the plasma profiles. This allows investigating the bias and discretization errors using Richardson extrapolation. It is shown that grid refinement and the number of employed Monte Carlo particles have the largest influence on the result, in agreement with similar studies of an ITER deuterium case. For the first time, numerical error bars on the entire simulated target profiles are determined showing that the largest numerical error is 17.9%, mainly due to the plasma grid discretization. On top, also numerical errors on simulated neutral pressures are investigated in detail, for which the statistical error is dominant. The analysis demonstrates which setup is needed to keep numerical errors limited: the SOLPS-ITER averaging procedure should be employed including enough EIRENE particles, and the involved grids should be sufficiently refined to reduce discretization errors.

Boeyaert, Dieter (ORCID:0000000309208660)↗

Scheduler Modeling of Distributed Energy Resources for Providing Ancillary Services

Distribution energy resources (DERs) have been integral components of modern power systems, and their capability to provide grid services has been widely studied. To promote the deployment of these resources in providing grid services in real-world utility operations, this paper proposes a day-ahead scheduler model for a distribution system connected DER plant. A certain amount of generation capacity of this DER plant is reserved for frequency services, and some ancillary services for the distribution system-including peak load reduction, voltage regulation, and power factor control-are integrated into the model. The model is tested on a real-world distribution system. From the simulation results, the energy and reserve schedule of the solar photovoltaic (PV) unit and battery energy storage system (BESS) can be determined, and voltage and power factor are well maintained. Additionally, in order to demonstrate the specific characteristics of the co-located and hybrid operation modes for the PV and BESS, these two modes are analyzed both theoretically and through real-time simulation. Simulation results show that most of PV's variability is transferred to the net power in the co-located mode, whereas it is transferred to the BESS in the hybrid mode. This proposed scheduler model and the comparison of co-located and hybrid modes can provide practical guidance for the applications of DER plant in the real-world utility.

14 SOLAR ENERGY↗

Data-driven modeling and control of dynamical systems using Koopman and Perron-Frobenius operators

This dissertation studies the data-driven modeling and control problem of nonlinear systems by exploiting the linear operator theoretic framework involving Koopman and Perro-Frobenius operator. A systematic linear-operator based controller design procedure has been established, which can be used to solve a variety of nonlinear control problems, including feedback stabilization using control Lyapunov functions, optimal quadratic regulation using Koopman eigenfunctions and convex optimization formulation of optimal control problem using P-F and Koopman operator approximation. As the core of data-driven modeling, we first propose a new algorithm for the finite-dimensional approximation of the linear transfer Koopman and Perron-Frobenius operator from time-series data. We argue that the existing approach for the finite-dimensional approximation of these transfer operators such as Dynamic Mode Decomposition (DMD) and Extended Dynamic Mode Decomposition (EDMD) do not capture two important properties of these operators, namely positivity and Markov property. The algorithm we propose preserves these two properties. We call the proposed algorithm as naturally structured DMD (NSDMD) since it retains the inherent properties of these operators. Naturally structured DMD algorithm leads to a better approximation of the steady-state dynamics of the system regarding computing Koopman and Perron- Frobenius operator eigenfunctions and eigenvalues. However, preserving positivity property is critical for capturing the real transient dynamics of the system. This positivity property of the transfer operators and it's finite-dimensional approximation play an important role for controller and estimator design of nonlinear systems. To solve the feedback stabilization problem for nonlinear control systems, we tried to take advantage of the Koopman operator framework. The Koopman operator approach provides a linear representation for a nonlinear dynamical system and a bilinear representation for a nonlinear control system. The problem of feedback stabilization of a nonlinear control system is then transformed to the stabilization of a bilinear control system. We propose a control Lyapunov function (CLF)-based approach for the design of stabilizing feedback controllers for the bilinear system. The search for finding a CLF for the bilinear control system is formulated as a convex optimization problem. This leads to a schematic procedure for designing CLF-based stabilizing feedback controllers for the bilinear system and hence the original nonlinear system. Another advantage of the proposed controller design approach outlined in this dissertation is that it does not require explicit knowledge of system dynamics. In particular, the bilinear representation of a nonlinear control system in the Koopman eigenfunction space can be obtained from time-series data. Next, we study the optimal quadratic regulation problem for nonlinear systems. The linear operator theoretic framework involving the Koopman operator is used to lift the dynamics of nonlinear control system to an infinite-dimensional bilinear system. The optimal quadratic regulation problem for nonlinear system is formulated in terms of the finite-dimensional approximation of the bilinear system. A convex optimization-based approach is proposed for solving the quadratic regulator problem for bilinear system. We applied a variety of examples and compared the simulation results between our framework and conventional LQR control using linearized model. For more general optimal control problems, we provide a density-function based convex formulation for the optimal control problem of the nonlinear system. The convex formulation relies on the duality result in the stability theory of a dynamical system involving density function and Perron-Frobenius operator. The optimal control problem is formulated as an infinite-dimensional convex optimization program. The finite-dimensional approximation of the optimization problem relies on the recent advances made in the data-driven computation of the Koopman operator, which is dual to the Perron-Frobenius operator. Simulation results are presented to demonstrate the application of the developed framework.

Huang, Bowen↗

Calibration of cohesive parameters for fracture test simulations of sub-sized bend specimens of AM steels

In this work, crack extensions in sub-sized side-grooved bend specimens of AM steels are examined with changing cohesive parameters. Two-dimensional FE analyses are first conducted to simulate crack extensions by nodal release. The simulation results indicate the near-tip maximum opening stress and separation work rate increase and then slightly decrease for the bend specimens. The hydrogen-charged bend specimens have lower near-tip maximum opening stresses and average separation work rates than those of the uncharged bend specimens. The changing near-tip maximum opening stresses and the separation work rates with increasing crack extension are determined as references for the changing cohesive strengths and energies, respectively. Two-dimensional FE analyses with different changing cohesive parameters are then performed. The simulation results with calibrated cohesive parameters can match well with the test results. The hydrogen-charged specimens have the lower changing cohesive strength vs crack growth curves compared with those of the uncharged specimens. The hydrogen-charged specimens have either lower or similar changing cohesive energy vs crack growth curves compared with those of the uncharged specimens. Finally, a three-dimensional FE analysis is conducted to simulate crack extension by nodal release in one bend specimen to examine the stress triaxialities in front of the growing crack fronts at different locations from the center plane to the planes near the side groove front with increasing crack extension to identify possible physical reasons for the changing cohesive parameters.

36 MATERIALS SCIENCE↗

Reachability Analysis for FollowerStopper: Safety Analysis and Experimental Results

Motivated by earlier work and the developer of a new algorithm, the FollowerStopper, this article uses reachability analysis to verify the safety of the FollowerStopper algorithm, which is a controller designed for dampening stop-and-go traffic waves. With more than 1100 miles of driving data collected by our physical platform, we validate our analysis results by comparing it to human driving behaviors. The FollowerStopper controller has been demonstrated to dampen stop-and-go traffic waves at low speed, but previous analysis on its relative safety has been limited to upper and lower bounds of acceleration. To expand upon previous analysis, reachability analysis is used to investigate the safety at the speeds it was originally tested and also at higher speeds. Two formulations of safety analysis with different criteria are shown: distance-based and time headway-based. The FollowerStopper is considered safe with distance-based criterion. However, simulation results demonstrate that the FollowerStopper is not representative of human drivers - it follows too closely behind vehicles, specifically at a distance human would deem as unsafe. On the other hand, under the time headway-based safety analysis, the FollowerStopper is not considered safe anymore. A modified FollowerStopper is proposed to satisfy time-based safety criterion. Simulation results of the proposed FollowerStopper shows that its response represents human driver behavior better.

Chou, Fang-Chieh↗

Optimal Decision Making in High-Throughput Virtual Screening Pipelines

ABSTRACT Effective selection of the potential candidates that meet certain conditions in a tremendously large search space has been one of the major concerns in many real-world applications. In addition to the nearly infinitely large search space, rigorous evaluation of a sample based on the reliable experimental or computational platform is often prohibitively expensive, making the screening problem more challenging. In such a case, constructing a high-throughput screening (HTS) pipeline that pre-sifts the samples expected to be potential candidates through the efficient earlier stages, results in a significant amount of savings in resources. However, to the best of our knowledge, despite many successful applications, no one has studied optimal pipeline design or optimal pipeline operations. In this study, we propose two optimization frameworks, applying to most (if not all) screening campaigns involving experimental or/and computational evaluations, for optimally determining the screening thresholds of an HTS pipeline. We validate the proposed frameworks on both analytic and practical scenarios. In particular, we consider the optimal computational campaign for the long non-coding RNA (lncRNA) classification as a practical example. To accomplish this, we built the high-throughput virtual screening (HTVS) pipeline for classifying the lncRNA. The simulation results demonstrate that the proposed frameworks significantly reduce the effective selection cost per potential candidate and make the HTS pipelines less sensitive to their structural variations. In addition to the validation, we provide insights on constructing a better HTS pipeline based on the simulation results.

97 MATHEMATICS AND COMPUTING↗

Simulating 50 keV X-ray Photon Detection in Silicon with a Down-Conversion Layer

Simulation results are presented that explore an innovative, new design for X-ray detection in the 20–50 keV range that is an alternative to traditional direct and indirect detection methods. Typical indirect detection using a scintillator must trade-off between absorption efficiency and spatial resolution. With a high-Z layer that down-converts incident photons on top of a silicon detector, this design has increased absorption efficiency without sacrificing spatial resolution. Simulation results elucidate the relationship between the thickness of each layer and the number of photoelectrons generated. Further, the physics behind the production of electron-hole pairs in the silicon layer is studied via a second model to shed more light on the detector’s functionality. Together, the two models provide a greater understanding of this detector and reveal the potential of this novel form of X-ray detection.

47 OTHER INSTRUMENTATION↗