[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120832-en":3,"doc-seo-120832-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120832,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","A Machine Learning Approach to Predicting Single Event Upsets","A single event upset (SEU) is a critical soft error in semiconductor devices caused by ionising particles in space environments, leading to memory bit flips and reduced reliability of stored information. In current practice, SEUs are detected only hours after they occur, creating significant safety risks for onboard systems. CREMER uses machine learning with positional data to predict SEU occurrence in advance, offering robustness, low cost, and scalability to improve memory reliability and support safer spacecraft operation.","A Machine Learning Approach to Predicting  \nSingle Event Upsets  \nArchit Gupta, Chong Yock Eng, Deon Lim Meng Wee, Rashna Analia Ahmed, See Min Sim  \nNanyang Technological University, Singapore {archit001, ceng006, dlim074, rashna002, [ssim033}@e.ntu.edu.sg](ssim033}@e.ntu.edu.sg)  \nAbstract—A single event upset (SEU) is a critical soft error that occurs in semiconductor devices on exposure to ionising particles from space environments. SEUs cause bit flips in the memory component of semiconductors. This creates a multitude of safety hazards as stored information becomes less reliable. Currently, SEUs are only detected several hours after their occurrence. CREMER—the model presented in this paper—predicts SEUs in advance using machine learning. CREMERuses only positional data to predict SEU occurrence—making it robust, inexpensive and scalable. Upon implementation, the improved reliability of memory devices will create a digitally safer environment onboard space vehicles.  \nI. INTRODUCTION  \nMany space bodies like satellites and the International Space Station (ISS) lie in the Low Earth Orbit (LEO), resulting in great exposure to cosmic microwave background radiation, solar radiation from the sun and Van Allen radiation. Although most radiation gets deflected by the Earth’s magnetosphere, high energy charged particles may still pass through and disrupt the operation of space devices. These charged particles, when passing through a medium, lose energy by ionisation and induce electron-hole pairs along their path. The interaction of electrons, protons, and heavy ions with integrated circuits could therefore lead to a total dose degradation, or worse, a single event effect—a class of radiation effects in electronic devices. In this research paper, we will be focusing on predicting single event upsets (SEU)—a subset of single event effects.  \nIn digital memory and logic devices, SEUs are nondestructive ‘soft’ errors. They normally appear as a bit flip in memory units or transient pulses in logic devices, and do not permanently destruct the functions of a device. Therefore, error detection and correction codes are frequently adopted to reduce the impact of SEUs. However, modern semiconductor devices tend to have tiny junction areas with proportionately small amounts of charge to control the state of memory units. This increases SEU disturbances because a single heavily charged particle passing through the junction would be sufficient to induce charge into the node and change its state, causing disruption of data stored at the node. As modern semiconductor devices are getting even smaller, predicting and mitigating SEUs is becoming an increasingly important  \nproblem. Our research is focused on mitigating the impact of single event upsets by employing machine learning. The model presented will allow the prediction of SEUs in memory units—prompting timely mitigation of the occurrence.  \nPrevious studies have been done on a similar problem [1]  \n[2], however, our approach differs by utilising a novel method on a more constrained dataset.  \nII. BACKGROUND  \nCurrent models used to predict SEUs are largely based on the transfer of energy from protons to electrical components as they pass through Very Large-Scale Integration (VLSI) devices [3] . These models are mostly tested in controlled environments with the aim of predicting critical energy levels of VLSI devices and to verify the strength of the shielding methods in place. The calculations behind these models are based on data collected in labs under the assumption that a device’s operation in such simulated environments is an indication of its operation in space. As a result of such assumptions, traditional physics-based models are not foolproof or robust.  \nLinear Energy Transfer (LET) is the fundamental idea behind several SEU prediction models. LET is the deposition of energy by high energy protons onto the cells of a semiconductor device as it pierces through the device. The amo","cbCailkd15eL01hc","https://ap.wps.com/l/cbCailkd15eL01hc","pdf",405159,1,4,"English","en",105,"# Introduction\n## Single event effects and SEUs\n## Motivation for prediction and mitigation\n# Background\n## Physics-based prediction models\n## LET and critical charge\n## Path-length distribution model\n## Bendel proton upset model\n# Methodology\n## Data","[{\"question\":\"What is a single event upset (SEU) and why is it critical?\",\"answer\":\"A single event upset is a soft error in semiconductor devices triggered by ionising particles, producing memory bit flips. It undermines the reliability of stored information and can create safety hazards.\"},{\"question\":\"Why are traditional physics-based SEU prediction models limited?\",\"answer\":\"They rely on energy-transfer and lab-simulated assumptions, which may not be robust for real space operation. Sensitive-volume simplifications can also reduce accuracy.\"},{\"question\":\"How does the CREMER model predict SEUs in advance?\",\"answer\":\"CREMER predicts SEU occurrence using machine learning based only on positional data. This design aims to be robust, inexpensive, and scalable for use in spacecraft systems.\"}]","A Machine Learning Approach to Predicting Single Event Upsets | PDF",1785732259,10,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":28},"a-machine-learning-approach-to-predicting-single-event-upsets","",{"@graph":36,"@context":84},[37,53,67],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":21},"https://docshare.wps.com/document/a-machine-learning-approach-to-predicting-single-event-upsets/120832/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":20},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What is a single event upset (SEU) and why is it critical?","Question",{"text":74,"@type":75},"A single event upset is a soft error in semiconductor devices triggered by ionising particles, producing memory bit flips. It undermines the reliability of stored information and can create safety hazards.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"Why are traditional physics-based SEU prediction models limited?",{"text":79,"@type":75},"They rely on energy-transfer and lab-simulated assumptions, which may not be robust for real space operation. Sensitive-volume simplifications can also reduce accuracy.",{"name":81,"@type":72,"acceptedAnswer":82},"How does the CREMER model predict SEUs in advance?",{"text":83,"@type":75},"CREMER predicts SEU occurrence using machine learning based only on positional data. This design aims to be robust, inexpensive, and scalable for use in spacecraft systems.","https://schema.org",{"og:url":52,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,127,130,133],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":29,"doc_module":4,"doc_module_name":46,"category_name":131,"show_sort_weight":29,"slug":132},"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":46,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]