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DOE OSTI2020

Effects of cryogenic temperature and grain size on fatigue-crack propagation in the medium-entropy CrCoNi alloy

CrCoNi-based high-entropy alloys have demonstrated outstanding mechanical properties, particularly at cryogenic temperatures. Here we investigate the fatigue-crack propagation properties of the equiatomic, single-phase, face-centered cubic, medium-entropy alloy (MEA), CrCoNi, that displays exceptional strength, ductility and toughness, all of which are enhanced at cryogenic temperatures. Fatigue-crack growth is examined, at a load ratio of 0.1 over a wide range of growth rates, from ~10 –11 to >10 –7 m/cycle, at room (293 K) and cryogenic (198 K, 77 K) temperatures for two grain sizes (~7 and 68 µm), with emphasis on near-threshold behavior. We find that the ΔK th fatigue thresholds are increased with decreasing temperature and increasing grain size: from 5.7 MPa√m at 293 K to 8 MPa√m at 77 K in the fine-grained alloy, and from 9.4 MPa√m at 293 K to 13.7 MPa√m at 77 K in the coarse-grained alloy. Mechanistically, transgranular cracking at 293 K transitions to a mixture of intergranular and transgranular at cryogenic temperatures, where the increased propensity of nano-twins appears to inhibit growth rates by deflecting the crack path. However, the main factor affecting near-threshold behavior is roughness-induced crack closure from interference between the crack flanks, which is enhanced by the rougher fracture surfaces at low temperatures, particularly in the coarser-grained microstructure. Here, fatigue-crack propagation behavior in CrCoNi is comparable to nickel-based superalloys but is superior to that of the high-entropy CrMnFeCoNi (Cantor) alloy and many high-strength steels, making the CrCoNi alloy an excellent candidate material for safety-critical applications, particularly involving low temperatures.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Vision–based Robust $\mathcal{H}$ ∞ Gain Scheduling Longitudinal and Lateral Following Controller for Autonomous Vehicles on Urban Curved Roads

Implementing advanced driver assistance systems (ADAS) in congested and intricate urban traffic scenarios poses significant challenges. To address the frequent stop–and–go motions exhibited by autonomous vehicles (AVs) navigating urban roads with changes in curvature, we propose a vision–based robust $\mathcal{H}$ ∞ adaptive cruise control system (ACC) for longitudinal control, plus a lane keeping assist system (LKAS) for lateral control. For the vision-based ACC, a weighted probability objective function for the vehicle following behavior is formulated. We incorporate $\mathcal{H}$ ∞ performance and gain scheduling techniques to mitigate the impact of uncertainty in visual sensor measurements. Furthermore, the optimal time headway is scheduled based on the velocity to ensure traffic flow efficiency and safety during the vehicle following process. For the LKAS, we introduce a road curvature estimation method that integrates lane and vehicle dynamics information to obtain the lateral and heading offsets. Next, the design criterion of the observer–based robust gain scheduling lateral motion controller is established by linear matrix inequality (LMI). Here, a series of experiments conducted within a camera–in–loop platform validate the proposed method.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Ship Motion Testing Needs Evaluation

The American Bureau of Shipping performed an evaluation of national maritime nuclear testing capabilities and determined there currently is an inability to test maritime nuclear power plants in a ship motion environment. A Ship Motion Test Facility (SMTF) is proposed to fill this gap. To inform design of this facility, this report documents an evaluation performed by a panel of technical experts that identifies key physical phenomena associated with maritime nuclear power plant operation that are important to safety and reliability and have a low state of knowledge. This evaluation concluded that all of the major test needs to understand a nuclear plant's behavior in a ship motion environment are for thermal-hydraulics related phenomena. Based on this finding, the evaluation panel concluded that the SMTF would not be required to use nuclear fuel to provide a heat source for the fluids. This would significantly decrease the cost, timeline, and complexity for this test facility to enable the advancement of maritime nuclear technology.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Overarching Properties as Means of Compliance: An Industrial Case Study

The Overarching Properties (OPs) have been created by an inter-national working group and are being evaluated by the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), industry, and other certifying agencies in an effort to streamline certification processes. Their intent is to facilitate the use of alternative approaches and to al-low flexibility to combine the system, software, and complex hardware certification. The hope is that the FAA may eventually establish an Advisory Circular that offers the OPs as a Means of Compliance (MoC) for software approval (and eventually systems and hardware) by showing the product possesses the three OPs: Intent (specification of the intended behavior), Correctness (implementation of the intended behavior) and Innocuity (safety of unintended behavior). In the certification community, there is still a concern about the practicability of using such high level properties in certification. This paper aims to address that concern by showing possession of the OPs in an industrial case study using assurance arguments. The two main contributions of this paper are: a certification process based on OPs as Means of Compliance, and a certification argument for an on-board physical model of an UAV, as industrial example. We pro-pose a hybrid approach for the certification process that combines OPs with existing certification standards. Thus, OPs can be used for parts of a system that uses technologies that are not supported by current standards or for which existing standards require additional effort without commensurate additional safety assurance.

certification↗

DOE OSTI2024

Implications of stop-and-go traffic on training learning-based car-following control

Learning-based car-following control (LCC) of connected and autonomous vehicles (CAVs) is gaining significant attention with the advancement of computing power and data accessibility. While the flexibility and large model capacity of model-free architecture enable LCC to potentially outperform the model-based car-following (CF) model in improving traffic efficiency and mitigating congestion, the generalizability of LCC for traffic conditions different from the training environment/dataset is not well-understood. Herein, this study seeks to explore the impact of stop-and-go traffic in the training dataset on the generalizability of LCC. It uses the characteristics of lead vehicle trajectories to describe stop-and-go traffic, and links the theory of identifiability (i.e., obtaining a unique parameter estimation result using sensor measurements) to the generalizability of behavior cloning (BC) and policy-based deep reinforcement learning (DRL). Correspondingly, the study shows theoretically that: (i) stop-and-go traffic can enable the property of identifiability and enhance the control performance of BC-based LCC in different traffic conditions; (ii) stop-and-go traffic is not necessary for DRL-based LCC to generalize to different traffic conditions; (iii) DRL-based LCC trained with only constant-speed lead vehicle trajectories (not sufficient to ensure identifiability) can be generalized to different traffic conditions; and (iv) stop-and-go traffic increases variance in the training dataset, which improves the convergence of parameter estimation while negatively impacting the convergence of DRL to the optimal control policy. Numerical experiments validate the above findings, illustrating that BC-based LCC entails comprehensive training datasets for generalizing to different traffic conditions, while DRL-based LCC can achieve generalization with simple free-flow traffic training environments. This further suggests DRL as a more promising and cost-effective LCC approach to reduce operational costs, mitigate traffic congestion, and enhance safety and mobility, which can accelerate the deployment and acceptance of CAVs.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2009

Proceedings of the Third International Workshop on Proof-Carrying Code and Software Certification

This NASA conference publication contains the proceedings of the Third International Workshop on Proof-Carrying Code and Software Certification, held as part of LICS in Los Angeles, CA, USA, on August 15, 2009. Software certification demonstrates the reliability, safety, or security of software systems in such a way that it can be checked by an independent authority with minimal trust in the techniques and tools used in the certification process itself. It can build on existing validation and verification (V&V) techniques but introduces the notion of explicit software certificates, Vvilich contain all the information necessary for an independent assessment of the demonstrated properties. One such example is proof-carrying code (PCC) which is an important and distinctive approach to enhancing trust in programs. It provides a practical framework for independent assurance of program behavior; especially where source code is not available, or the code author and user are unknown to each other. The workshop wiII address theoretical foundations of logic-based software certification as well as practical examples and work on alternative application domains. Here "certificate" is construed broadly, to include not just mathematical derivations and proofs but also safety and assurance cases, or any fonnal evidence that supports the semantic analysis of programs: that is, evidence about an intrinsic property of code and its behaviour that can be independently checked by any user, intermediary, or third party. These guarantees mean that software certificates raise trust in the code itself, distinct from and complementary to any existing trust in the creator of the code, the process used to produce it, or its distributor. In addition to the contributed talks, the workshop featured two invited talks, by Kelly Hayhurst and Andrew Appel. The PCC 2009 website can be found at http://ti.arc.nasa.gov /event/pcc 091.

Ewen, Denney, W.↗

DOE OSTI2017

Development of a bayesian belief network model for the software reliability assessment of nuclear digital I and C safety systems - 206

Since the digital instrumentation and control systems are expected to play an important role for the safety systems in nuclear power plants (NPPs), the need has emerged to not only establish a basis for incorporating software behavior into digital I and C system reliability models, but also to quantify the failure probability of the software used in NPP digital protection systems. In this study, a Bayesian belief network (BBN) model is developed to quantitatively assess software reliability by estimating the number of faults in a software program considering its software development life cycle (SDLC). The model structure and parameters are established based on the information applicable to NPP safety-related systems and the evidence used to construct and quantify the BBN model was collected from three stages of expert elicitation. The software failure probability is estimated from the number of residual defects in a software program at the end of SDLC phase. As a case study, the BBN model was applied to quantify the software reliability of a typical digital protection software having the size of 50 function points and having the Medium development and validation and verification (V and V) qualities. The developed model can be applied to estimate the failure probability for both developing and deployed safety-related NPP software, and such results can be used to evaluate the quality of the digital I and C systems in addition to estimating potential reactor risk due to software failure. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

A Simulation-Based Dynamic Approach for External Flooding Analysis in Nuclear Power Plants

All nuclear power plants must consider and evaluate external flooding risks such as local intense precipitation, dam failure, and coastal flooding due to storm surge or tsunami. While these events could challenge off-site power and other plant structure integrity, threaten plant safety systems and components, and limit plant access, they are more than often qualitatively regarded as risk insignificant and screened out from detailed evaluation and quantification. The recent lessons learned from the Fukushima seismic/tsunami initiated nuclear accident (2011), the Fort Calhoun (2011), Vermont Yankee (2013), Arkansas Nuclear One (2013), and St. Luice (2014) flooding events showed otherwise. However, developing an external flood model with traditional event tree/fault tree approach as in a static probabilistic risk assessment (PRA) model could be difficult to accurately represent plant system and component behavior and reliability of manual actions during an ever-progressing flood event. The plant response to external flood may be highly spatial- and time- dependent and subject to the hydrological and hydraulic characteristics of the flood event. Such unique challenges prompt the investigation of using the simulation-based dynamic analysis approaches for external flood risk assessment. Simulation methods can better illustrate the performance of structures, systems, and components during an external flooding event. A general framework to perform a simulation-based dynamic flooding analysis is presented in this paper with the sub-tasks of flood hazard analysis, flood fragility analysis, plant response modeling, safety margin analysis or PRA quantification. A new type of State PRA modeling technique is introduced to incorporate time-related interactions such as those from 3D simulations into a traditional PRA model.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Design and implementation of a real-time underwater acoustic telemetry system for fish behavior study and environmental sensing

Underwater acoustic telemetry is an important tool for studying the behavior of aquatic animals and assessing the environmental impact of man-made structures such as water power turbines. However, current design of the acoustic telemetry system lacks the ability to transmit collected data continuously in real-time and requires manual retrieval of the recorded measurements, leading to a long delay of data retrieval, high operational cost associated with manpower as well as safety risk for the operators. In addition, there is no efficient way to monitor the status of the acoustic telemetry system, including acoustic transmitters and receivers. For example, if multiple receivers in an array fail, the detection efficiency could be significantly reduced. Herein, we developed a cloud-based, real-time underwater acoustic telemetry system that can be used to estimate behavior or survival of tagged aquatic animals and monitor environmental parameters in near-real-time (< 2 hours). The system incorporates microcontrollers and integrated circuits to create real-time data communication and processing units with a cloud-based service that processes the transmitted data stream to derive behavior and survival information of the tagged animals.

Yang, Yang↗

DOE OSTI2017

Integrated Solutions for Interim Used Fuel Management: From Pool Unloading to Safe Delivery to Recycling or Repository Facilities - 17235

Safe management of used nuclear fuel (UNF) is key to the survival of the nuclear industry. That is why it is more important than ever to have a consent-based, practical, credible, and sustainable roadmap for managing the back-end of the nuclear cycle. Worldwide UNF Light Water Reactors (LWR) inventories are currently around 200,000 tons and are estimated to grow to more than 350,000 tons by 2030, and operating nuclear reactors in the U.S. continue to discharge UNF every 18 to 24 months. International experience has demonstrated that the development of a permanent geological repository can be a multi-decade process, especially in the face of public acceptance challenges. Meanwhile, the solution for permanent disposal of UNF in the U.S. is moving at a glacial pace. As a result, industrial stakeholders have been forced to find practical interim UNF storage solutions in order to continue safely operating their reactors. Among those interim solutions are the cask- or canister-based dry storage systems that have dramatically increased in the last 10 years as they provide flexibility for expansion with a low up-front investment. With interim dry storage in place for more than 30 years, our industry is entering a new phase as we are forced to prepare for a few more decades before geological repositories begin operating. Consequently, interim dry storage has to be extended for 80 years or more. Thus, new considerations have to be taken into account to ensure the safety of this stored used fuel: - Interim storage systems are aging; - High burn-up fuel behavior overtime is uncertain; - Used fuel is losing its self-protection; - The number of shutdown sites without a fuel transfer facility, such as a pool, is increasing; - Some owners of Independent Spent Fuel Storage installation (ISFSI) at shutdown sites are not nuclear operators anymore. With increasing uncertainties, AREVA TN -- based on its long expertise with used fuel transportation and interim storage systems -- is adapting its portfolio to develop integrated and flexible solutions that will remove the burden of interim used fuel management from nuclear operators. AREVA TN is developing comprehensive solutions to reduce risks including the continued supply of proven safe high-performance dry storage systems; on-site services to safely transfer used fuel from pool to pad; the optimization of fuel heat load in the storage pool and pad; innovative aging management services including inspection, monitoring and repair; a realistic solution for consolidated interim storage with a priority to remove Used Nuclear Fuel stored in dry storage systems from shutdown sites; world-class transport and logistics services to safely move the used fuel from nuclear reactor sites to consolidated storage and repository or recycling as applicable, and turnkey management of shutdown ISFSIs. Due to the lack of an available path for transporting used fuel away from reactors, nuclear operators are faced with many challenges and growing uncertainties. Our presentation will describe the practical solutions developed and being developed in order to manage used fuel on behalf of nuclear operators and allows them to continue focusing on the important job of producing carbon-free clean energy. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2020

Composite Overwrapped Pressure Vessel (COPV) Damage Tolerance Life Analysis Methodology and Test Best Practices

The NASA Engineering and Safety Center (NESC) Deputy Director requested an independent assessment to develop data to understand the limitations of linear elastic fracture mechanics (LEFM) computational methods used to predict fatigue crack growth rate (da/dN) behavior of small detectable cracks in thin metal liners for composite overwrapped pressure vessels (COPVs). The NESC assessment team was also requested to demonstrate a test-based methodology for validating damage tolerance requirements for COPVs with elastically responding metal liners where LEFM methods are not appropriate. This report contains the outcome of the NESC assessment.

Composite Overwrapped Pressure Vessels; Linear Ela↗

NASA NTRS2012

Using Game Theoretic Models to Predict Pilot Behavior in NextGen Merging and Landing Scenario

In this paper, we present an implementation of the Semi Network-Form Game framework to predict pilot behavior in a merging and landing scenario. In this scenario, two aircraft are approaching to a freeze horizon with approximately equal distance when they become aware of each other via an ADS-B communication link that will be available in NextGen airspace. Both pilots want to gain advantage over the other by entering the freeze horizon earlier and obtain the first place in landing. They re-adjust their speed accordingly. However, they cannot simply increase their speed to the maximum allowable values since they are concerned with safety, separation distance, effort, possibility of being vectored-off from landing and possibility of violating speed constraints. We present how to model these concerns and the rest of the system using semi network-from game framework. Using this framework, based on certain assumptions on pilot utility functions and on system configuration, we provide estimates of pilot behavior and overall system evolution in time. We also discuss the possible employment of this modeling tool for airspace design optimization. To support this discussion, we provide a case where we investigate the effect of increasing the merging point speed limit on the commanded speed distribution and on the percentage of vectored aircraft.

Yildiz, Yildiray↗

NASA NTRS2020

Composite Overwrapped Pressure Vessel (COPV) Damage Tolerance Life Analysis Methodology and Test Best Practices: Appendices

The NASA Engineering and Safety Center (NESC) Deputy Director requested an independent assessment to develop data to understand the limitations of linear elastic fracture mechanics (LEFM) computational methods used to predict fatigue crack growth rate (da/dN) behavior of small detectable cracks in thin metal liners for composite overwrapped pressure vessels (COPVs). The NESC assessment team was also requested to demonstrate a test-based methodology for validating damage tolerance requirements for COPVs with elastically responding metal liners where LEFM methods are not appropriate. This document contains the appendices to the main report.

Composite Overwrapped Pressure Vessels; Linear Ela↗

DOE OSTI2025

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full-Waveform Inversion

Concrete is a vital material in construction—especially in the nuclear industry, where it is used in critical structures such as containment vessels. Over time, concrete can degrade due to harsh operational and environmental conditions, necessitating that its elastic properties be accurately evaluated to ensure structural integrity and safety. Traditional nondestructive evaluation methods such as ultrasound-based techniques often rely on simplifying assumptions that may not hold true for concrete. This paper presents an advanced ultrasound-based method that uses elastic full-waveform inversion (EFWI) to create detailed images of concrete’s mechanical properties. By accurately modeling wave behaviors such as scattering and reflection, we aim to overcome the limitations of conventional ultrasonic-based methods. In this work, the imaging problem involved reconstructing the various elastic properties of a heterogenous concrete block with three steel rebars embedded in it. The ultrasonic measurements were synthetically generated from multiple sources and receivers, and the reconstruction process was performed using a gradient-based optimization algorithm. Our approach leveraged EFWI to reconstruct high-resolution images of the pressure wave speed, shear wave speed, and density. Multiple misfit functions—including L2-norm, cross-correlation (CC), and L1-norm—combined with total variation (TV) regularization and parameter constraints using a Sigmoid function—were explored for the reconstruction. The results demonstrated that using the L1-norm misfit function in conjunction with TV regularization and Sigmoid constraints significantly improved the reconstruction quality in comparison to traditional methods. This approach provided clearer images with fewer artifacts and better captured background heterogeneity. Our findings highlight that, when properly designed, EFWI carries great potential for providing comprehensive, more accurate, and more reliable assessments of concrete conditions, as is crucial for the maintenance and safety of nuclear power plant structures.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Corrosion behavior of Monofrax K-3 refractory in borosilicate-based model low activity waste glass melts

Owing to its good chemical and thermal durabilities at high temperatures, Monofrax K-3 refractory is widely used in nuclear waste vitrification as a lining material in melting vessels. However, the corrosion of K-3 refractory during the vitrification of nuclear waste is a serious problem because it affects the melter's safety, performance, and lifetime. Therefore, in the present study, we have focused on unearthing the impact of glass network formers, such as SiO 2 , B 2 O 3 , and Al 2 O 3 , in a model nuclear waste glass composition on the corrosion of Monofrax K-3 refractory. The corrosion tests have been performed per ASTM C621 at 1150°C for 5 days. The dimensional measurements on corroded K-3 refractory suggest that Al 2 O 3 and SiO 2 tend to reduce the refractory corrosion (neck loss), with the effect of Al 2 O 3 being significant. A corroded region on the K-3 refractory at the melt–refractory interface is observed. The corrosion occurs via a coupling of the melt infiltration induced by a capillary effect and the dissolution of Al, Mg, and Fe components from K-3 into the melt through chemical reactions. A Cr-rich layer is retained on the glass contact surface of the corroded K-3 refractory.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Comprehensive Battery Safety Risk Evaluation: Aged Cells versus Fresh Cells Upon Mechanical Abusive Loadings

Abstract Despite their wide applications, lithium‐ion batteries (LIBs) have been struggling with their safety risks arising from different lifetime stages. Here, the NCMA pouch cell is taken as an example, and the safety of both fresh and aged cells from three milestone stages, that is, internal short circuit (ISC) triggering risk, ISC mode, and the subsequent thermal runaway (TR) consequence is investigated. By combining mechanical abusive testing and physics‐based models on commercialized cells with various states‐of‐health (SOH) and states‐of‐charge, it is discovered that the ISC triggering delays with the decay of SOH and soft ISC mode will be triggered more frequently, which is mainly due to the mechanical behaviors of the current collectors. The temperature rises and peak temperature during the subsequent TR also become milder for aged cells due to the reduced capacity and deterministic soft ISC process. Results here provide a mechanistic explanation of the safety risk comparison between the fresh and aged cells, offering cornerstone guidance to the evaluation and design of next‐generation safer LIBs.

25 ENERGY STORAGE↗

NASA NTRS2004

Scatter in Carbon/Silicon Carbide (C/SiC) Composites Quantified

Carbon-fiber-reinforced silicon carbide matrix (C/SiC) composites processed by chemical vapor infiltration are candidate materials for aerospace thermal structures. Carbon fibers can retain properties at very high temperatures, but they are known to have poor oxidation resistance in adverse, high-temperature environments. Nevertheless, the combination of CVI-SiC matrix with higher stiffness and oxidation resistance, the interfacial coating, and additional surface-seal coating provides the necessary protection to the carbon fibers, and makes the material viable for high-temperature space applications operating under harsh environments. Furthermore, C/SiC composites, like other ceramic matrix composites (CMCs), exhibit graceful non-catastrophic failure because of various inherent energy dissipating mechanisms. The material exhibits nonlinearity in deformation even at very low stress levels. This is the result of the severe matrix microcracking present in the as processed composite because of large differences between the coefficients of thermal expansion of the fiber and the matrix. Utilization of these advanced composites in next generation space vehicles will require innovative structural configurations, updated materials, and refined analyses. Structural safety issues for these vehicles are in direct competition with performance and cost. One would have to quantify the uncertainties associated with the design using formal probabilistic methods. Specifically four fundamental aspects on which analyses are based-- (1) loading conditions, (2) material behavior, (3) geometrical configurations, and (4) structural connections between the composite components and baseline structure--are stochastic in nature. A direct way to formally account for uncertainties is to develop probabilistic structural analysis methods where all participating variables are described by appropriate probability density functions. The present work, however, focuses on analyzing the stochastic material behavior of these advanced composites using formal probabilistic analysis methods. Often, some of the desirable property characteristics that allow composites to offer advantages over conventional structural materials (like tailoring of composite properties) and the complexity are in fact responsible for their greater statistical variability and the requirements for more characterization tests. Composite properties are anisotropic as well, having different properties in different directions. This means that characterization of a property such as stiffness--which will vary greatly depending on the orientation of the fiber relative to the direction of the testing--must be repeated for several different directions and loading conditions. The fabrication process for composites also introduces statistical variations in properties and geometry. A composite part is produced in a number of steps, each of which introduces statistical variability. The matrix is usually produced from a combination of raw materials; and the fiber, which has its own set of properties, is often coated or surface treated, introducing yet another source of variability.

Murthy, Pappu L. N.↗

DOE OSTI2022

Inferring safety critical events from vehicle kinematics in naturalistic driving environment: Application of deep learning Algorithms

Advances in sensing technology has enabled the collection of countless terabytes of second-by-second kinematics data. Such data provides opportunities for real-time monitoring of driving behavior and identification of safety critical events (SCEs) including crashes and near crashes. The concept of volatility is relevant in this context, which identifies instability and erratic variations in driving behavior prior to involvement in SCEs. This study utilized vehicle kinematics from a large-scale naturalistic driving data to develop a deep learning approach based on 1D convolutional neural networks (CNN) for inferring SCEs. The data are unique in the sense that such accurate pre-crash data at high fidelity are not available in traditional crash repositories. This study contributes to the literature by providing a first attempt at predicting responses to SCEs by developing deep learning-based CNN architectures using novel driving volatility based kinematic thresholds for a sample of 9553 events. The key contribution lies in developing a volatility-based CNN input layout that is acceptable to CNN schemes and represents the motion kinematics such as speed, acceleration and volatility measures. Several 1D-CNN architectures were developed using layers, numbers of convolutions, layer patterns, and kernels. Shallow and deep architectures were tested, revealing higher accuracy of shallow architectures in detecting SCEs. The optimal number of epochs were identified using an early stopping method while the CNN performance was improved by increasing the number of epochs. The ensemble CNN had the highest predictive accuracy of 95.6% for detection of crashes and near crashes, which was 2.5% higher than the optimal CNN using 20% hold out test data. The ensemble CNN also outperformed classical machine learning models and model performance reported in past studies on detection of SCEs. Finally, these results have implications for identification of safety hotspots and providing real-time alerts and warnings in connected and highly automated vehicle environment including society of automotive engineers levels 3–5.

42 ENGINEERING↗