Arjun Earthperson

North Carolina State University | NCSU · Department of Nuclear Engineering

Advanced nuclear reactors are ushering in a transformative era in the nuclear energy sector, characterized by generational advancements in safety, efficiency, and sustainability. Central to realizing the advanced reactor philosophy is the integration of digital instrumentation and control (I&C) systems, which are critical for enhancing the operatio...

This paper delves into the critical need for a simulation-based framework to aid the evaluation of the reliability of digital Instrumentation and Control (I&C) systems in advanced nuclear power plants, as the industry transitions from analog to digital systems. With limited operational history for digital I&C systems, simulation-based methods are e...

This pilot study addresses the challenge of optimizing variable ordering in binary decision diagrams (BDDs) for fault tree analysis within probabilistic risk assessment, with a specific focus on addressing the unique challenges posed by advanced nuclear reactors. Advanced reactors, including small modular reactors, present novel operational and saf...

Aalo Atomics, a mission-oriented startup is dedicated to deploying commercially viable microreactors rapidly into the market to support timely transition to clean energy generation. A critical part of our rapid deployment strategy is our Adopt, Adapt, and Advance approach (the 3-A approach) which entails 1) leveraging (adopting), to the maximum ext...

Ensuring the reliability and effectiveness of nuclear safety systems is paramount for preventing severe accidents and ensuring operational safety. This study introduces a method for quantifying the unavailability margins of safety systems, employing inverse estimation techniques to deduce event sequence frequencies. The proposed method is demonstra...

In the rapidly evolving technological landscape, probabilistic risk assessment (PRA) is increasingly essential in supporting decision-making and engineering processes across multiple industries, particularly in the nuclear sector. Central to the development and safety assurance of nuclear power plants (NPPs), PRA is crucial in navigating the challe...

Probabilistic Risk Assessment (PRA) is a pivotal process, serving as the cornerstone of risk-informed decision-making for critical infrastructure sectors such as aerospace, chemical, and nuclear industries. It provides a dynamic engineering and scientific framework that underpins these vital systems, from their initial design phases to eventual dec...

This thesis introduces an integrated framework for enhancing the safety assessment of fission batteries—nuclear reactors designed with battery-like features for autonomous operation— by combining two advanced risk modeling techniques: the dual error propagation graph (DEPM) and event modeling risk assessment using linked diagrams (EMRALD). Fission...

Probabilistic Risk Assessment (PRA) is a pivotal process, serving as the cornerstone of risk-informed decision-making for critical infrastructure sectors such as aerospace, chemical, and nuclear industries. It provides a dynamic engineering and scientific framework that underpins these vital systems, from their initial design phases to eventual dec...

This pilot study addresses the challenge of optimizing variable ordering in binary decision diagrams (BDDs) for fault tree analysis within probabilistic risk assessment, with a specific focus on addressing the unique challenges posed by advanced nuclear reactors. Advanced reactors, including small modular reactors, present novel operational and saf...

Advanced nuclear reactors are ushering in a transformative era in the nuclear energy sector, characterized by generational advancements in safety, efficiency, and sustainability. Central to realizing the advanced reactor philosophy is the integration of digital instrumentation and control (I&C) systems, which are critical for enhancing the operatio...

This paper conducts a focused probabilistic risk assessment (PRA) on the reliability of commercial off-the-shelf (COTS) drones deployed for surveillance in areas with diverse radiation levels following a nuclear accident. The study employs the event tree/fault tree digraph approach, integrated with the dual-graph error propagation method (DEPM), to...

Transportation systems play a pivotal role in modern society, but they are not without inherent risks and inefficiencies. This paper explores the integration of Probabilistic Risk Assessment (PRA) and Machine Learning (ML) techniques to enhance safety and cost optimization in hazardous materials (HAZMAT) transportation. Traditional PRA methods, whi...

Probabilistic Risk Assessment (PRA) tools are crucial in the nuclear, aerospace, maritime, and chemical industries. This paper presents OpenPRA, an innovative, open-source, web-based platform designed to address the limitations of current Probabilistic Risk Assessment (PRA) tools. OpenPRA offers a collaborative and flexible environment that support...

Wearable devices and fitness trackers have gained popularity in healthcare and telemedicine as tools to reduce hospitalization costs, improve personalized health management, and monitor patients in remote areas. Smartwatches, particularly, offer continuous monitoring capabilities through step counting, heart rate tracking, and activity monitoring....

Probabilistic risk assessment (PRA) tools are used to model complex systems using event and fault trees. The goal is to evaluate some metrics that assist the decision-makers in improving their design, like the failure probability of the top event and the importance factors. The evaluations should also cover the uncertainty and sensitivity analysis....

Advanced reactor designs, such as Nuscale's NuScale Power Module (NPM) and X-energy's Xe-100, maximize the use of off-the-shelf components manufactured and shipped to the site. Small modular reactors will employ factory fabrication compared to the large-scale construction of nuclear power plants [1] [2]. Consequently, stakeholders will have to expa...

Research into digital instrumentation and control (I&C) upgrades is an important topic for the nuclear industry. Despite their advantages, there has been limited implementation of digital I&C systems in nuclear power plants (NPPs). Digital I&Cs can have complex failure modes, including software and hardware related common cause failures (CCFs), whi...

Current probabilistic risk assessment (PRA) quantification engines should be updated since they have served the community for over a decade without significant updates. Today's personal computers are like the supercomputers of twenty years ago. Also, most of the PRA quantification engines lack the applicability of efficient computation. Some readil...

This paper develops a methodology for quantifying software common cause failure parameters (CCFs) in nuclear power plants' digital instrumentation and control systems. Probabilistic Risk Assessment (PRA) techniques are used to support the transition of analog instrumentation and control systems to digital in nuclear power plants. The hardware compo...

Nowadays, probabilistic risk assessment (PRA) has contributed prominently to many technological fields, assisting decision-makers and engineers in assessing and mitigating risks inherent in their systems and designs. In the nuclear industry, PRA has become crucial in all nuclear power plant (NPP) design stages, informing engineers and decision-make...

This paper presents a limited scope dynamic probabilistic risk assessment (D-PRA) on the sur-vivability of commercial of the shelf (COTS) drones tasked with surveilling areas with varying radiation levels after a nuclear accident. The D-PRA is founded on a discrete-dynamic event tree (D-DET) approach, which couples with the OpenEPL error propagatio...

The notion of nuclear reactors with battery-like capabilities, called fission batteries, puts forth system re- quirements and design constraints that have so far been unseen in the nuclear power production industry. Such restrictions require fission batteries to be modular, integrated, autonomous, tamper-proof (i.e., resilient, fault- tolerant, all...

The development of the nuclear industry’s Probabilistic Risk Assessment (PRA) has significantly contributed to the design, reliability, and safety of nuclear power plants (NPP). Today, PRAs form integration in all nuclear power plant development stages, including design, licensing, operation, maintenance, and decommissioning. Many legacy PRA tools...

The spread of the COVID-19 pandemic across the world has presented a unique problem to researchers and policymakers alike. In addition to uncertainty around the nature of the virus itself, the impact of rapidly changing policy decisions on the spread of the virus has been difficult to predict. Using an epidemiological Susceptible-Infected-Recovered...

Today, Probabilistic Risk Assessment (PRA) plays a vital role in assuring mission success for robotic and crewed missions alike. Current-day PRA techniques integrate multimodal, often black-box analyses to build comprehensive risk profiles. This paper describes a review and verification study of the “Nuclear Risk Assessment for the Mars 2020 Missio...

We define supply chains (SCs) as sequences of processes that link the demand and supply of goods or services within a network. SCs are prone to shortages in delivering their output goals due to several factors such as personnel undersupply, inefficient processes, policy failure, equipment malfunction, natural hazards, pandemic outbreaks, power outa...

The approval process from the U.S. Nuclear Regulatory Commission (NRC) for nuclear power plants is sequential. It involves several government bodies such as the Advisory Committee on Reactor Safeguards (ACRS), public meetings, and hearings. If the submissions made to the NRC do not contain enough information to meet the regulation requirements, the...

Adoption of electronic Commercial-Off-The-Shelf (COTS) parts in various industrial products is rapidly increasing due to the accessibility and appealing lower cost of these commodities. Depending on the type of application, having an accurate understanding of the COTS failure information can be crucial to ensure the reliability and safety of the fi...

This project attempts to provide a reliably accurate indoor localization service to complement the outdoor GPS systems so widely prevalent today. Using WiFi based RSSI fingerprinting and machine learning, we build and test Bayesian models in at-home and public locations, with f-measures of 0.893 for 14 points of interest in a hallway and 0.994 with...

This paper discusses improvements made to the LCDK development workflow through a series of compute optimizations, implementation of I 2 C, UART and GPIO communication protocols, and the introduction of Deep Neural Networks(DNN) exported from Tensorflow. We have been able to achieve between 5x-7.5x speedup in FFT execution times, 2x speedup in math...