Sandia Labs FY21 LDRD Annual Report

FY21 ANNUAL REPORT

Using additive manufacturing to rapidly develop specialized alloys for spray processing. Plasma spray is a useful advanced manufacturing process for depositing thick coatings of various materials with unique structure-property relationships. However, a primary roadblock to the successful integration of spray coatings, especially for complex or custom high-performance refractory-based alloys, is the limited available options for starting feedstock materials. In this LDRD project, researchers used a novel high-throughput metal additive manufacturing approach to rapidly create refractory-based high entropy alloy feedstock for thermal spray applications intended for downstream use in plasma spray processing applications. The success of this method readily expands the feedstock and alloy options available for use in plasma spray processing, enabling researchers to make custom alloys from elemental feedstock. (PI: Shaun Whetten) Developing integrated cybersecurity safety and security models for energy systems. Protecting the electric grid is crucial to national security. This project, part of the Resilient Energy Systems LDRD Mission Campaign, investigated a new cyber security capability that integrated advanced hazards analysis, risk assessment, safety, and cyber security models into a risk-based approach for cybersecurity resilience. This methodology used the causal logic model Systems-Theoretic Process Analysis (STPA) to link digital control susceptibilities to facility hazards and consequences. The resulting STPA causal analysis provided a systematic approach for constructing Bayesian Networks (BN) to model consequence-based security scenarios in higher fidelity. As a stand-alone new capability, this approach illustrates how cyber- based attacks relate to industrial hazards and provided a way to incorporate industrial process design into security analysis. When combined with risk-informed management methodologies, this STPA/BN- based approach offers a comprehensive risk-informed cybersecurity analysis that allows decision-makers to prioritize based on understanding the potential system-level risks. When combined with well-known The process used by the LDRD team to create refractory-based high entropy alloy feedstock for thermal spray applications.

cyber security methods (e.g., MITRE’s ATT&CK framework), the approach could allow for predicting the difficulty of an attack—forming the basis of more justifiable and efficient designs to protect the electric grid and associated energy systems. (PI: Andrew Clark) MITRE’s ATT&CK framework in conjunction with cyber resiliency metrics and Bayesian Networks can be used to predict how an adversary accomplishes the unsafe control actions and the difficulty of an attack.

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LABORATORY DIRECTED RESEARCH & DEVELOPMENT