About

Tarasankar DebRoy is a Professor of Materials Science and Engineering at Pennsylvania State University. His research focuses on computational materials processing, particularly the application of numerical transport phenomena and optimization in welding and additive manufacturing. He develops models that compute critical factors affecting metallurgical product quality, such as temperature and velocity fields, cooling rates, and solidification parameters, by solving tens of billions of equations efficiently. His models are uniquely structured for integration with genetic algorithms and other search engines, enabling bi-directional simulations that help tailor product attributes, optimize production variables, reduce defects, and improve overall product quality. Professor DebRoy has made significant contributions to the field, including developing the first rigorous numerical models of heat and fluid flow in 3D printing to reduce distortion and defects, and creating comprehensive models for laser-fired aluminum-silicon contact geometry in photovoltaic devices. He has pioneered models for controlling weld geometry and cooling rates during welding, estimating temperatures during laser welding, and understanding the role of surface active elements in steels. His work also includes a three-dimensional visco-plastic-flow and heat transfer model for friction stir welding. DebRoy is the founding editor of the 'Science and Technology of Welding and Joining' and has held various leadership roles, including chairing the Research and Development committee of the American Welding Society and organizing international conferences on welding research. His extensive research and modeling efforts have advanced the understanding and optimization of welding and additive manufacturing processes.

Research topics

• Computer Science
• Engineering
• Artificial Intelligence
• Materials science
• Metallurgy
• Mechanical engineering
• Manufacturing engineering
• Systems engineering
• Risk analysis (engineering)
• Industrial engineering
• Process engineering
• Management science
• Data science

Selected publications

• Building blocks of a digital twin

  Elsevier eBooks · 2026-01-01

  book-chapter1st authorCorresponding
  PublisherDOI

• Design for Additive Manufacturing

  2026-02-06

  otherSenior author

  The design for additive manufacturing is important for several reasons. The design starts with a computer-aided design file that includes geometric data such as the size, shape, and orientation, the additive manufacturing process, process parameters to be used, and other data. The unique capabilities of additive manufacturing are important for design. Constraints play a crucial role in the design of parts for additive manufacturing because they affect the quality, functionality, and cost of the parts. In additive manufacturing, a wide variety of materials including metals and alloys, polymers, ceramics, and composites are used for fabricating parts. Topology optimization in additive manufacturing is concerned with various shapes and orientations of the part or structure, the distribution of material within it, and the size and placement of openings and voids while meeting certain performance requirements and constraints. The design for additive manufacturing affects material and energy usage, waste, and recycling. These factors affect sustainability.

  PublisherDOI

• Common Defects in Additively Manufactured Parts

  2026-02-06

  otherSenior author

  Part quality, reliability, and serviceability of additively manufactured parts are often affected by many types of common defects. Solidification cracking, liquidation cracking, and ductility dip cracking are the three types of cracking that occur in many additively manufactured alloy parts. Alloys with poor weldability typically exhibit high cracking susceptibilities during additive manufacturing. Understanding the mechanisms of the formation of these cracks is important for their prevention. The surface roughness of the additively manufactured metallic parts affects their performance and impedes the successful inspection of components. Many metallic feedstocks contain volatile alloying elements. Familiar examples are magnesium and zinc in aluminum alloys, chromium and manganese in steels, and aluminum in titanium alloys. The chapter also discusses the nondestructive testing of parts for pores, cracks, and inclusions to ensure their fitness for service. Defect mitigation by post-processing often involves hot isostatic pressing, heat treatment, and surface modifications.

  PublisherDOI

• Current status, research needs, and outlook

  Elsevier eBooks · 2026-01-01

  book-chapter1st authorCorresponding
  PublisherDOI

• Feedstocks and Processes for Additive Manufacturing of Ceramic Parts

  2026-02-06

  otherSenior author

  This chapter explores the importance of the additive manufacturing of ceramics. It focuses on the commonly used ceramic feedstocks. The chapter describes the working principles of commonly used additive manufacturing processes for ceramics. It also explores the properties of the additively manufactured ceramic parts. The chapter also focuses on the common defects in the ceramic parts and the common applications of additively manufactured ceramic parts. Metals and polymers are the most widely used materials in additive manufacturing. A variety of inorganic materials are commonly used to make ceramic parts by additive manufacturing. They are alumina, zirconia, silica, silicon carbide, silicon nitride, and calcium phosphate-based biomaterials. The evolution of properties and defects of ceramic parts made by stereolithography, binder jetting, robocasting, and laminated object manufacturing are affected by the sintering process. 3D printing has been increasingly used in the production of ceramic parts due to its ability to create complex geometries and customize designs.

  PublisherDOI

• Front Matter

  2026-02-06

  otherSenior author

  The prelims comprise: Half-Title Page Title Page Copyright Page Contents Preface

  PublisherDOI

• Mechanistic Models, Machine Learning, and Digital Twins in Additive Manufacturing

  2026-02-06

  otherSenior author

  In additive manufacturing (AM), structurally sound and reliable parts are produced and certified by trial and error for each part, material, and process variant. This chapter examines the progress made and the opportunities and challenges in the mechanistic modeling of various important aspects of metal printing. It discusses the common machine learning algorithms, indicate the availability of open-source algorithms and codes, describes important applications in AM, and provides worked out examples to show how machine learning calculations can be done using open-source codes. The chapter also discusses the most important building blocks of a digital twin of AM and their functions. A combination of machine learning, models, experiments, and big data in AM can create a digital twin of 3D printing which has the potential to address many issues in AM. These powerful emerging digital tools can provide important insights about the process as well as products that are not obtainable by any other means.

  PublisherDOI

• Current Status, Trends, and Prospects

  2026-02-06

  otherSenior author

  This chapter provides an outline of the activities and trends that are useful for a critical assessment of the technology and its potential for future growth. The growth of the number of patents in recent years shows the continuing innovations for the refinement of technology. The data on the growth of peer-reviewed literature and patents also show the interest and vitality of the field and its prospects. The chapter also presents several impactful case studies that show the growing applications of additive manufacturing. Significant ongoing research in the fields of printing biological materials, affordable housing, foods, solid-state batteries, new alloys, and multiple materials all point to expanding the diversity of printed products and innovative applications for 3D printing in a variety of industries. Integration of emerging digital technology, achieving unique combination of desirable properties, and 4D printing are examples of important recent trends in additive manufacturing.

  PublisherDOI

• Heat Transfer in Additive Manufacturing

  2026-02-06

  otherSenior author

  In additive manufacturing, a laser beam, or an electron beam, or an electric arc is used as a heat source to melt a powder or wire feedstock layer-upon-layer to construct a three-dimensional part. This chapter examines the fundamentals of heat transfer in powder bed fusion (PBF) and directed energy deposition (DED) processes. It focuses on laser, electron beam, and arc heat sources with powder and wire feedstocks. The chapter explains the heat absorption mechanisms for PBF and DED processes and the factors important for heat transfer. It presents several heat conduction calculations for both PBF and DED processes to estimate thermal cycles, fusion zone size, and cooling rates for different alloys and process conditions. The chapter includes several calculations to predict the maximum velocities inside the molten pool, which provide important insight into convective heat transfer.

  PublisherDOI

• Residual Stresses and Distortion

  2026-02-06

  otherSenior author

  This chapter helps the readers to understand different mechanisms of evolution of residual stresses and distortion during additive manufacturing (AM). There are three key physical factors responsible for the origin of residual stresses and distortion in AM: thermal effects, effects of plasticity and flow stresses, and solid-state phase transformation. The chapter describes commonly employed measurement techniques of residual stresses and distortion in AM parts along with their relative advantages and disadvantages. The measurement techniques include: hole drilling and curvature methods, diffraction techniques, ultrasonic and magnetic methods, and indentation testing. The chapter introduces back-of-the-envelope calculations to quickly compare susceptibility to distortion for different AM processes, process parameters, and alloys. It also discusses variations in residual stresses and distortion for different AM processes, process parameters, and printing strategies. The chapter highlights several techniques for reducing or controlling residual stresses and distortion in AM parts.

  PublisherDOI

Frequent coauthors

• Todd Palmer

  Pennsylvania State University

  45 shared

• T. Mukherjee

  43 shared

• A. De

  Indian Institute of Technology Bombay

  38 shared

• J. W. Elmer

  Lawrence Livermore National Laboratory

  36 shared

• Wei Zhang

  27 shared

• S. A. David

  25 shared

• H. K. D. H. Bhadeshia

  Queen Mary University of London

  23 shared

• Huiliang Wei

  Nanjing University of Science and Technology

  21 shared

Awards & honors

• Founding Editor, Science and Technology of Welding and Joini…
• Chair, Research and Development committee, American Welding…
• Chair 9th International Conference on Trends in Welding Rese…
• Co-Chair, 5th, 6th, 7th, 8th and 10th International Conferen…