Parameter Sensitivity Study Research Articles

Studying Dynamical and Hydraulic Characteristics of the Hydraulically Suspended Passive Shutdown Subassembly (HS-PSS) and Validating with a Prototypic Test Sample

The pool-type demonstrative China Fast Reactor 600 (CFR-600) adopted a series of improved safety designs, among which the hydraulic suspended passive shutdown subassembly (HS-PSS) is employed for inherent safety enhancement, especially suitable against unprotected loss of flow accident (ULOF). In this article, functional requirements for HS-PSS design in hydro-dynamic aspects are proposed, with the corresponding performance indicators discussed. To address these functional requirements, qualitative analysis on the equilibrium solution properties of the nonlinear dynamical model equation of the hydraulic moving body (HMB) in the HS-PSS are conducted, which leads to the determination of an applicable design parameter domain of the HMB for its practical design from the broad range of structural and parametric design options available for HS-PSS. Furtherly, hydraulically characterizing and modeling the constituent paths and consequent fluid network, hydraulic characteristics of the HS-PSS, as well as the coupled hydro-dynamic motion behaviors of the HMB for suspension and dropping states, were simulated and test-validated. Considering the HS-PSS hydro-dynamic behaviors, key indicators such as critical flowrate, drop time, hydraulic self-tightening performance, as well as the hydraulic characteristics curve are for fulfilling the functional requirements. Meanwhile, through sensitivity study of some structural parameters‘ impact on hydraulic characteristics, some most sensible structural parameters for adjusting and optimizing detailed design are observed. The work is quite significant in supporting the conceptual design of the HS-PSS as well as its engineering improvement.

On the stabilizing contribution of different grid‐forming controls to power systems

AbstractThe increasing penetration of power‐electronics interfaced resources brings new challenges regarding the small‐signal stability of power systems. To address this issue, grid‐forming (GFM) controlled converters have emerged as an alternative to their conventional grid‐following counterparts. This paper investigates the mechanisms behind converters driven stability and quantifies the stabilizing effect of GFM controls. The linearized state‐space model of different combinations of control strategies is analysed in a multi‐infeed system considering various operating points. Through a parametric sensitivity study and an examination of the participation factors of key eigenvalues of the linearized models, it is confirmed that GFM controls contribute to system stabilization. Moreover, this paper demonstrates that this stabilizing effect varies significantly depending on the specific GFM control implemented: whether a current control loop is used or not notably impacts stability.

Wave overtopping discharges at rubble mound structures in shallow water

Wave overtopping of coastal structures has been studied using physical model experiments with rubble mound breakwaters in shallow water. The mean overtopping discharge is determined for three different foreshore slopes and various hydrodynamic conditions. The hydrodynamic results confirm that energy is transferred to low-frequency waves in very shallow water and that the short waves are in phase with the lower-frequency waves in very shallow water. As a result, the extreme waves (e.g. 2% exceedance wave height) become relatively large in very shallow water due to the energy of the low-frequency waves affecting thereby the wave overtopping. To estimate the amount of energy at the low-frequency waves, an expression is derived which reasonably accurately predicts the low-frequency wave energy (RMSE of 0.06). Considering the non-dimensional overtopping discharge, the existing formulations for the non-dimensional mean wave overtopping discharge perform poorly to reasonably in shallow water with RMSLE ranging from 1.04 to 2.92. A parameter sensitivity study shows that the short-wave steepness, relative crest height and the low-frequency wave height are the most important parameters when predicting the mean overtopping discharge in shallow water. When including the short-wave steepness and relative crest height in an empirical formulation the RMSLE for the current dataset reduces to 0.69. A further increase in accuracy is found when the low-frequency wave height and 2% exceedance wave height are included (RMSLE 0.64).

Quantifying the effect of scanning parameters on digital volume correlation analysis for in situ X-ray imaging of concrete

The potential effects of X-ray Computed Tomography (XCT) scan settings on the kinematic field computed via Digital Volume Correlation (DVC) are discussed in this paper. A parametric sensitivity study was conducted, including a series of acquired XCT scans, probing the same volume of interest (VOI) of a concrete specimen, and applying various combinations of XCT scan settings. Different values were adopted for the number of projections acquired, the exposure time and the pixel size. The DVC results revealed a linear correlation between the mean normalised correlation residuals, designating the quality of the correlation and the reliability of the computed kinematic field and the scanning parameters. Gaussian and median filters were applied to the raw data to explore the effect of image noise smoothness in the DVC analysis. The significant reduction noted for the mean normalised correlation residuals was not accompanied by similar levels of change for the corresponding error uncertainties, as defined by the displacement magnitude. The concept was tested against a realistic loading scenario, where the DVC kinematic fields, computed for various XCT “recipes”, were compared. Slim differences in the distribution of the mean minimum principal strain were observed.

Mechanical properties study of fiberglass reinforced flexible pipeline in marine applications

ABSTRACT A mechanical properties study of fibereglass reinforced flexible pipe (FGRFP) in marine applications is proposed based on the reinforced layer interface structure design, the anisotropic layer section mechanical performance test, and the structural strength analysis under the laying operation condition. Based on laboratory tests and referencing ASTM and DNV regulations, the technical design indexes of flexible marine pipe that meet strength requirements have been provided. Through tests, the maximum yield tension of FGRFP is 89.8kN, the ultimate curvature is 3.3 rad/m, the bending moment is 2312.2Nm, the torsion angle is 0.32 rad, and the torque is 2610.4Nm. Based on numerical simulation, static analysis can identify weak points in flexible pipelines. Especially, the feasibility of FGRFP structural section design was verified through dynamic analysis under the combined action of waves and currents. Finally, parameter sensitivity studies were conducted, including the effects of wave/flow direction, wave height, and period.

Hybrid thermochemical cycle for cold and electricity cogeneration: Experimental and numerical analyses of the process behavior and expander-reactor coupling

The valorization of waste heat to respond to the increase demand on electricity and cooling is an important energetic challenge. For this purpose, a hybrid thermochemical cycle is proposed. This discontinuous sorption cycle is based on reversible endothermic/exothermic solid–gas reactions, and it is able to recover medium grade waste heat (between 150 and 250 °C) to valorize it in a second step by providing cold production at its endothermic component and mechanical work thanks to the integration of an expander on the gas line. Moreover, the two-step operation leads to a storage functionality. This paper presents an experimental study of this new hybrid cycle prototype in different operating conditions, and a sensitivity study of the design parameters of the prototype performed through a steady state model. The experimentation shows the influence of the electrical load applied to the generator on the coupling between the expander and reactor, by affecting the rotational speed, the torque of the expander and the pressure of the reactor. The analysis of the experimental results highlighted the effect of two main limitations in the prototype: the internal leaks on the expander side (unlubricated scroll expander) and the heat transfer on the reactor side. A numerical parametric study is done on these two parameters, showing the possibility of cogenerating 125 W of mechanical power and 2.3 kW of cold for defined enhanced parameters of the prototype. These promising results prompt the next step of conducting a detailed exergetic analysis of the cycle. This analysis will aim to identify the primary sources of exergy destruction and to explore ways for reducing them by minimizing main irreversibilities in the cycle.

Sensitivity study of process parameters of wire arc additive manufacturing using probabilistic deep learning and uncertainty quantification

This study employs a deep learning (DL) based stochastic approach to comprehensively interpret the effects of current intensity and velocity variations on temperature evolutions and cooling rates in the wire arc additive manufacturing (WAAM) process of a thin wall. Uncertainty raised from process parameters, material properties, and environmental conditions significantly impacts the final product quality. Furthermore, understanding the relationship between the process and temperature evolution within the WAAM process is complex. This study contributes to quantifying the uncertainty to the final product quality, such as temperature evolutions and cooling rates via a fast and accurate DL-based surrogate model. This contribution helps to precise adjustments and optimizations to enhance the overall WAAM process. Initially, a DL-based surrogate model is constructed using data obtained from a high-fidelity validated finite element (FE) model, ensuring an impressive 99% accuracy compared to the FE model while reducing computational costs. Subsequently, probabilistic methods are used to characterize uncertainties in current intensity and velocity, and the Monte-Carlo method is applied for uncertainty propagation. The findings illustrate that small variations in the input parameters can lead to significant fluctuations in temperature evolutions. Additionally, a sensitivity analysis is conducted to precisely quantify the influence of each input parameter. Finally, an uncertainty reduction is performed to enhance the variation of cooling rate. In general, this study is expected to make precise adjustments and optimizations to enhance the overall WAAM process for better quality of printed piece.

Thermal integration process for waste heat recovery of SOFC to produce cooling/H2/power/freshwater; cost/thermal/environmental optimization scenarios

High-temperature fuel cells (HT-FCs) indeed hold significant promise for enhancing energy systems' efficiency and environmental sustainability. Consequently, there is growing interest in exploring and developing innovative strategies to optimize the integration of heat recovery processes with HT-FC technology. The current research presents an innovative and environmentally friendly poly-generation unit that integrates advanced subprocesses to generate essential products. These final products include electricity, refrigeration, pure water, and hydrogen. This study signifies a significant step towards sustainable and efficient energy production while meeting diverse needs for different utilities. The design unit incorporates a novel modified dual ejector-based organic flash cycle, reverse osmosis water purification, and a water electrolyzer for hydrogen extraction, all integrated with a high-temperature solid oxide fuel cell. Energy, exergy, economic, and environmental (4E) analysis is conducted to thoroughly evaluate the proposed plan. Furthermore, a comprehensive parametric analysis and sensitivity study are performed to pinpoint the key design parameters of the poly-generation unit. To attain the optimal operational status of the poly-generation unit, a three-objective NSGA-II optimization technique is employed to fine-tune the system's performance within the exergy-cost-environmental framework. This approach aims to strike a balance between maximizing efficiency, minimizing costs, and reducing environmental impact for sustainable operations. In addition, a net present value analysis spanning a 20-year timeframe was conducted to assess the profitability of the devised unit. Based on the findings, it is evident that the sensitivity index of the fuel cell operating temperature carries substantial importance, registering a notable value of 0.60. Additionally, the optimization outcomes reveal the system's enhanced performance metrics: an exergetic efficiency of 41.11 %, a unit cost of 58.96 $/GJ, and a carbon dioxide emission reduction rate of 418 kg/MWh. Also, the unit's payback period is shortened from 11.33 years to 8.817 years. Moreover, it improved the unit's sustainability index and net present value, raising them from 1.544 to 4.98 M$ to 1.66 and 7.38 M$.

Emergoenvironmental analysis and sustainable flexible peaking of a novel solar-assisted solid oxide fuel cell cogeneration system

The development of green and sustainable conversion technologies is imperative to alleviate the current severe energy and environmental crises and to achieve the goal of carbon neutrality. This project presents a novel cogeneration system that integrates a solid oxide fuel cell afterburning system, an energy recovery system, and a parallel heating system equipped with multistage utilization, solar-assisted, and flexible peaking technologies. Following the establishment and validation of the system, power source analysis, parameter sensitivity studies, three-objective optimization, and internal exergy flow investigation are carried out. Subsequently, the positive impacts of multistage utilization, solar-assisted, and flexible peaking technologies, as well as the thermoeconomic and emergoenvironmental operating characteristics of the system, are discussed. The numerical results demonstrate that the emergoenvironmental factor and emergy environmental impact difference of the system are 70.15 % and 82.52 %, and the energy efficiency is improved by 1.41 %∼19.09 %, respectively, compared with similar solid oxide fuel cell systems, confirming its favorable thermodynamic performance and emergoenvironmental impact. The system achieves daily heating savings of 3302 kWh and life cycle economic benefits of $19,310,524, with a repayment of the investment cost in 4.17 years, reflecting considerable economic benefits. This project also demonstrates exergy flow, module defects, and improvement mechanisms from the perspective of emergoenvironmental, providing a valuable reference for the promotion of green energy.

Carbon dioxide capture by aqueous glucosamine solutions: Pilot plant measurements and a theoretical study

AbstractA comprehensive investigation of the potential of aqueous glucosamine solutions as an eco‐friendly solvent for CO2 capture was performed. It includes an experimental study in a pilot plant setup and a theoretical analysis with a rate‐based model. The model was validated against the measured column profiles of temperature and CO2 concentration in both liquid and gas phases. Model‐based parameter sensitivity studies revealed inherent challenges for an effective absorption process. A slow reaction rate and suboptimal chemical equilibrium conditions were identified as key limitations, restricting the absorption efficiency and CO2 loading capacity of the glucosamine solution. Furthermore, an analysis of the dissociation constant of this novel absorbent was performed and its significance with respect to the (limited) performance, capability, and efficiency evaluation was highlighted.

Effect of Radial Neutron Reflector on the Characteristics of Nuclear Fuel Burn-Up Wave in a Fast Neutron Energy Spectrum Multiplying Medium: A Consistent Parametric Approach

Abstract The influence of radial neutron reflector on the build-up and propagation of a nuclear fuel burn-up wave in a fast multiplying medium is investigated using a consistent parametric approach. Coupled multigroup neutron diffusion equations with a burn-up evolution model are simulated on the two-dimensional cylindrical reactor geometry with azimuthal symmetry. Uranium–plutonium transmutation model is considered, and the simulation is performed by using the finite element multiphysics software package comsol. Transient characteristics of the burn-up wave are represented by two new parameters, namely, transient time (TT) and transient length (TL). TT and TL are defined as the time and distance required for the burn-up wave to attain its steady-state nature. Steady-state phases are characterized in terms of wave velocity, full width half maximum (FWHM), and full width 10% of maximum (FW10M). A sensitivity study of steady-state and transient parameters is conducted for the different values of radial reflector thickness. The potential relevance of these characterization parameters on the development of optimal geometrical configuration of radial neutron reflector in breed and burn (B&B)-based reactor design is addressed based on the sensitivity study.

High‐Throughput Screening of Low‐Bandgap Organic Semiconductors for Photovoltaic Applications: In the Search of Correlations

Low‐bandgap nonfullerene acceptors (NFAs) offer a unique potential for photovoltaic (PV) applications, such as transparent PV and agrivoltaics. Evaluating each new PV system to achieve the optimum thickness, microstructure, and device performance is, however, a complex multiparametric challenge with large time and resource requirements. Herein, the PV potential of low‐bandgap donor and NFA materials by combining high‐throughput screening and statistical methods is evaluated. The use of thickness gradients (20–600 nm) facilitates the fabrication of more than 2000 doctor‐bladed devices from 24 different low‐bandgap blend combinations. The corresponding power conversion efficiencies varies significantly, from 0.06% to 10.45% across materials and thicknesses. The self‐consistency of the large dataset allows to perform a parameter sensitivity study as well as parameter correlation analysis. These reveal that the choice of materials and energy alignment‐related features (i.e., electron affinity offset, ionization energy offset, bandgap, and energy loss) has the largest influence on final device performance, while processing conditions appear less important for the final efficiencies. Our study demonstrates that high‐throughput experimentation is a perfect match for correlation analyses in order to gain a statistically meaningful understanding of these systems, potentially accelerating the discovery of new materials.

Identifying sub-cascades from the primary damage state of collision cascades

The morphology of a collision cascade is an important aspect in understanding the formation of defects and their distribution. While the number of sub-cascades is an essential parameter to describe the cascade morphology, the methods to compute this parameter are limited. We present a method to compute the number of sub-cascades from the primary damage state of the collision cascade. Existing methods analyze peak damage state or the end of ballistic phase to compute the number of sub-cascades which is not always available in collision cascade databases. We use density based clustering algorithm from unsupervised machine learning domain to identify the sub-cascades from the primary damage state. To validate the results of our method we first carry out a parameter sensitivity study of the existing algorithms. The study shows that the results are sensitive to input parameters and the choice of the time-frame analyzed. On a database of 100 collision cascades in W, we show that the method we propose, which analyzes primary damage state to predict number of sub-cascades, is in good agreement with the existing method that works on the peak state. We also show that the number of sub-cascades found with different parameters can be used to classify and group together the cascades that have similar time-evolution and fragmentation. It is seen that the number of SIA and vacancies, % defects in clusters and volume of the cascade, decrease with increase in the number of sub-cascades.

Probabilistic pile reinforced slope stability analysis using load transfer factor considering anisotropy of soil cohesion

AbstractA probabilistic limit equilibrium framework combining empirical load transfer factor and anisotropy of soil cohesion is developed to conduct pile‐reinforced slope reliability analysis. The anisotropy of soil cohesion is determined conditioned on that the thrust force direction is parallel to the major principal direction and it is easily combined with load transfer factor, which are related with soil parameters, and pile parameters. The proposed method is illustrated against a homogeneous soil slope. The sensitivity studies of pile parameters on factor of safety (FS; calculated at respective means of soil parameters) and β demonstrated that the anisotropy of soil cohesion tends to pose significant effect on reliability index β than on FS. The effect of anisotropy of soil cohesion on FS is found to be slightly different under different pile locations, whereas its effect on β is observed to be least if piles are drilled at the middle part of slope and more significant effect is observed when piles are drilled at the lower and upper part of slope. The plots from the sensitivity studies provide an alternative tool for pile designs aiming at the target reliability index β. The proposed method contributes to the pile‐reinforced slope stability within limit equilibrium framework.

Energy loss analysis in cavitation flow of a continuous-resistance trim

Energy loss is generated by phase transition and work done on the continuous-resistance trim (CRT) in cavitation flow. This study aims to explore an enhanced CRT design to minimize energy loss in cavitation flow. Four key parameters, specifically orifice shape, inlet velocity, aperture and tilt angle, which have been proven to impact flow in CRT, are examined using a validated numerical method to assess their effects on energy loss in cavitation flow. Furthermore, based on a parametric sensitivity study, an improved design is proposed to control cavitation and reduce energy loss. Findings indicate that changes in orifice shape notably influence the flow area and throttling effect, which are closely connected to energy loss in cavitation. A critical inlet velocity of v1/v0 = 0.5 triggers cavitation occurrence. An orthogonal design method employing L16(45) array is used to analyze the effects of apertures, resulting in the identification of a preferred group with lower energy loss. A larger tilt angle β1/β0 effectively suppresses cavitation generation and significantly decreases energy loss. Finally, an enhanced CRT design is proposed, incorporating a circular (chamfer) orifice shape, an inlet velocity of v1/v0 = 0.3, the preferred aperture group (No.1), and a tilt angle of β1/β0 = 0.66, this improved design showcases reduced energy loss compared to the original CRT design. The findings of this study have broad applications in guiding the implementation of throttling components to suppress cavitation and minimize energy loss.

Impact response of composite energy absorbers based on foam-filled metallic and polymeric auxetic frames

In this paper, an innovative concept is proposed, based on the hexachiral auxetic frames filled with foams with enhanced energy absorption capabilities. Numerical assessments of the composite foam-filled auxetic absorbers, of pure foam blocks and unfilled auxetic frames for metallic and polymeric material combinations were accomplished considering a case of localized impact. The energy absorbed by the composite absorbers are found superior to the sum of the energies absorbed by constituent elements tested separately with clear advantages also at the level of the specific energy absorbed per unit mass. The interactions between the two constituents are analyzed and discussed. An experiment considering a 3D-printed polymeric hexachiral frame filled with open-cell soft polyurethane foam under localized impact is conducted to validate the numerical approach. Eventually, a parametric sensitivity study is conducted numerically to illustrate the effects of geometrical parameters on the energy absorption capacity. Overall, the results confirm the potential and the great design flexibility of the concept, provides the guidelines to design advanced energy absorbing system, underlies the importance of the combination between the frame and foam properties and the effect of the main geometrical parameters on the performance.

Structural Performance and Design of Aluminum Claddings Subjected to Windborne Debris Impact

Aluminum cladding panels have been used in some of the most iconic buildings around the world due to their durability, aesthetic appeal, and longevity. These panels play a critical role as the first line of defense against external forces such as wind and rain; therefore, the appropriateness of the design and resilience of aluminum cladding panels must be ensured. Previous researchers have conducted very minimal research on aluminum panels subjected to windborne debris impact. Their scope was limited to studying the response of panels when they are targeted at the center. The influence of various structural and load-related parameters on the response of such claddings has yet to be investigated. Furthermore, no design guidelines are readily available that engineers can use to predict the response of aluminum cladding panels when subjected to such loads considering various conditions (location of impact, projectile’s material, angle of impact, velocity of impact, unsupported length, and the geometry of the panels). The main aim of this paper was to develop some design guidelines that engineers can use to predict the response of aluminum cladding panels exposed to windborne debris impact. To achieve this, a series of parametric studies was conducted to generate a data bank. These parametric studies were performed with the help of a robust numerical model that has been validated with experimental results. The parametric sensitivity study revealed that the angle of impact was the most influential parameter, causing an 80% reduction in the peak impact force with a 50% decrease in the angle. The velocity, plate thickness, location of impact, and unsupported length also significantly influenced the panel’s response. The alloy type emerged as a dominant factor affecting the maximum and residual deflections. Regression equations were formulated based on the generated dataset to accurately predict the peak impact force, maximum central deflection, and residual deflection of solid aluminum cladding panels. The proposed prediction equations offer a better alternative to experimental testing.

New Simple Analytical Surge/Swab Pressure Model for Power-Law and Modified Yield-Power-Law Fluid in Concentric/Eccentric Geometry

The axial movement of pipe in and out of the well generates positive (surge) and negative (swab) pressures that will impact the well pressure. When the swab and surge effects cause well pressures outside the allowable operational limits, wellbore instability (well collapse/well fracture), kick, and induced drill string sticking issues will occur. The problems increase the operational and nonproductive time-related costs. Consequently, the drilling budget rises significantly. It is therefore, imperative to predict the differential pressures in order to mitigate the problems. Even though several models have been developed in the past, models work for the considered experimental setup and conditions. In this paper, a simple analytical model was derived for eccentric/concentric annuli. The fluid rheological behaviors were assumed to be described by power law and yielded power-law. The model is derived based on a steady state condition, and the effects of tripping speed, the power-law fluids, the yield-power-law fluids rheological parameters, and well geometries are considered. The model is compared with experimental data from the literature and with the existing model. Parametric sensitivity studies have been conducted. Results show that the model prediction exhibited quite good performance, with an average percentile error deviation of 9.9% and 6.2% for the power-law and yield-power-law fluids, respectively. However, more testing is required to determine the model’s limitations and application.

Reliability Evaluation and Maintenance Planning for Systems With Load-Sharing Auxiliary Components

In many engineering systems, aside from the main component fulfilling the essential functions, a number of auxiliary components are configured to protect the main component and improve the reliability of the system. In actual operation, the failure or state change of the auxiliary components may affect the reliability both the main component and the remaining operational auxiliary components. However, the structure and dependence between the auxiliary components has been ignored in the existing studies. To fill this gap, we consider a system with a main component and a protective auxiliary subsystem. The latter is a load-sharing <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\bm{k}$</tex-math></inline-formula> -out-of- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\bm{n}$</tex-math></inline-formula> system, that is, there is dependence between the auxiliary components. For such a system, an opportunistic inspection and preventive maintenance strategy is proposed. Then, we derive the system reliability using the Laplace transforms and the matrix method. The long-run average cost of the system is then derived, based on which the optimal maintenance problem is formulated and solved by an enumeration method. A numerical example, together with sensitivity studies of some model parameters, shows how the evolution of the parameters influences the optimal maintenance strategy. Finally, the model is extended by introducing periodic inspection and preventive maintenance strategy for main component, and the two strategies are compared.

A Sensitivity Study of Key Parameters on the Efficiencies and Energy Losses of Organic Redox Flow Batteries

Organic redox flow batteries (ORFB) are promising cost-competitive technologies for large-scale energy storage. At the unit cell scale, the battery performance is controlled by the combined effects of key parameters of microstructure design, physicochemical properties of organic molecules, mass transport, operating conditions, and membrane properties. However, a comprehensive study of how these parameters could affect the overall performance of ORFB has not been done. To address this gap, this work presents a sensitivity study of 12 key parameters on the battery efficiencies and energy losses of ORFB by using a validated numerical model for the Dihydroxyphenazine (DHP) family. The 12 key parameters include the specific area of microstructure; mass transfer rate; diffusivity, viscosity, reaction transfer coefficient, the reaction rate constant, standard potential, and electronic conductivity of DHP anolyte; operation conditions such as initial concentration of active species, pump rate, and applied current; and membrane electronic conductivity. In total, we generated 15,360 combinations of the 12 key parameters. These data are split into 15 groups with each having a fixed current density and flow rate and 1024 random parameter combinations of the remaining 10 parameters. All these parameters are then sent to the validated ORFB model developed in Comsol to predict the coupled flow, reaction, and transport processes at 38 pre-defined SOC between 0.025 and 0.85. We then output the total potential, equilibrium potential, activation potential, and concentration potential for charge (19 SOC) and discharge (19 SOC) from the model to further calculate the Coulombic Efficiency, Energy Efficiency, Voltage Efficiency, and System Efficiency as well as the energy losses contributed by equilibrium, activation, concentration, and ohmic losses. With these calculated efficiencies and the relative importance of energy losses, we used a deep neural network (DNN) to fit the relationship between the input 12 parameters (15,360 combinations), and the model calculated 4 efficiencies/relative ratios of energy losses. A sensitivity score is then calculated based on the DNN model and key factors controlling the ORFB performance are determined.