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Cyber-Informed Engineering is a framework which allows engineers to build resiliency to the impacts of cyber attack into engineered systems starting in the early design phases. This article introduces the framework and provides a description of some of its principles and resources for learning more.
An encoder–decoder neural network has been used to examine the possibility for acceleration of a partial integro-differential equation, the Fokker–Planck–Landau collision operator. This is part of the governing equation in the massively parallel particle-in-cell code XGC, which is used to study turbulence in fusion energy devices. The neural network emphasizes physics-inspired learning, where it is taught to respect physical conservation constraints of the collision operator by including them in the training loss, along with the ℓ 2 loss. In particular, network architectures used for the computer vision task of semantic segmentation have been used for training. A penalization method is used to enforce the ‘soft’ constraints of the system and integrate error in the conservation properties into the loss function. During training, quantities representing the particle density, momentum and energy for all species of the system are calculated at each configuration vertex, mirroring the procedure in XGC. This simple training has produced a median relative loss, across configuration space, of the order of 10 –4 , which is low enough if the error is of random nature, but not if it is of drift nature in time steps. The run time for the current Picard iterative solver of the operator is O(n 2 ), where n is the number of plasma species. As the XGC1 code begins to attack problems including a larger number of species, the collision operator will become expensive computationally, making the neural network solver even more important, especially since its training only scales as O(n). Here, a wide enough range of collisionality has been considered in the training data to ensure the full domain of collision physics is captured. An advanced technique to decrease the losses further will be subject of a subsequent report. Eventual work will include expansion of the network to include multiple plasma species.
Accurate and synchronized timing information is required by power system operators for controlling the grid infrastructure (relays, Phasor Measurement Units (PMUs), etc.) and determining asset positions. Satellite-based global positioning system (GPS) is the primary source of timing information. However, GPS disruptions today (both intentional and unintentional) can significantly compromise the reliability and security of our electric grids. A robust alternate source for accurate timing is critical to serve both as a deterrent against malicious attacks and as a redundant system in enhancing the resilience against extreme events that could disrupt the GPS network. To achieve this, we rely on the highly accurate, terrestrial atomic clock-based network for alternative timing and synchronization. In this paper, we discuss an experimental setup for an alternative timing approach. The data obtained from this experimental setup is continuously monitored and analyzed using various time deviation metrics. We also use these metrics to compute deviations of our clock with respect to the National Institute of Standards and Technologys (NIST) GPS data. The results obtained from these metric computations are elaborately discussed. Finally, we discuss the integration of the procedures involved, like real-time data ingestion, metric computation, and result visualization, in a novel microservices-based architecture for situational awareness.
An electric power grid is exceedingly faced with extreme events, such as physical attacks and natural disasters. In comparison, the underground natural gas pipeline-based transportation network is considered less vulnerable to such environmental threats. We consider that the overhead power transmissions can be hardened by replacing segments of electric power system with underground natural gas pipelines as an energy transportation system to counter effect extreme events which can damage interdependent infrastructures severely. This project investigates an extension of the power system planning problem considering extreme events and identifies the feasibility of solving this problem with advanced modeling and optimization methods. The proposed planning framework is formulated as a two-stage optimization problem. It is found that the integrated planning introduces the additional cost of pipeline planning and the operation constraints into the power system planning. However, gas pipelines are generally less exposed to extreme events, which can provide a more resilient power transmission for supplying the electrical loads. It is with this potential for enhancing the power grid resilience that the proposed integrated expansion of electricity and natural gas system is considered an optimal layout for the transportation of energy.
A new method for calculating the three-dimensional inviscid surface streamlines and streamline metrics using Cartesian coordinates and time as the independent variable of integration has been developed. The technique calculates the streamline from a specified point on the body to a point near the stagnation point by using a prescribed pressure distribution in the Euler equations. The differential equations, which are singular at the stagnation point, are of the two point boundary value problem type. Laminar heating rates are calculated using the axisymmetric analog concept for three-dimensional boundary layers and approximate solutions to the axisymmetric boundary layer equations. Results for elliptic conic forebody geometries show that location of the point of maximum heating depends on the type of conic in the plane of symmetry and the angle of attack, and that this location is in general different from the stagnation point. The new method was found to give smooth predictions of heat transfer in the nose region where previous methods gave oscillatory results.
The economic recovery of petroleum, like other fossil fuels, is limited. Although the current price of oil has dramatically dropped due to increased production and new production methods, it is not expected to remain low for an extended period of time as demand increases. While new methods of obtaining these fossil energy reserves are constantly being invented and introduced, the cost of production generally continues to increase. New sources of energy such as fracking and oil shale or oil sands recovery can produce enormous amounts of energy, but at a severe cost. The current estimate on energy return for energy invested for oil shale for instance is just barely over 1, meaning that for every barrel of energy produced by oil shale there was nearly a barrel of energy invested to recover it. Furthermore, these new technologies are often constantly under attack for environmental concerns (especially given the poor ratio of energy conversion), while conventional oil is regarded as dangerous due to lack of domestic supply and susceptibility to foreign intervention that compromises overall national security. Alternatives to a petroleum-based supply of fuel are a potential route to address these issues, although they must also be economically feasible. The fuels industry is forced to consider these issues in addition to federal mandates intended to gradually diversify our fuel sources.
The effects of stainless steel exposure to iodinated water is a concern in developing the Integrated Water System (IWS) for Space Station Freedom. The IWS has a life requirement of 30 years, but the effects of general and localized corrosion over such a long period have not been determined for the candidate materials. In 1978, Umpqua Research Center immersed stainless steel 316L, 321, and 347 specimens in a solution of deionized water and the Space Shuttle microbial check valve resin. In April 1990, the solution was chemically analyzed to determine the level of corrosion formed, and the surface of each specimen was examined with scanning electron microscopy and metallography to determine the extent of general and pitting corrosion. This examination showed that the attack on the stainless steels was negligible and never penetrated past the first grain boundary layer. Of the three alloys, 316L performed the best; however, all three materials proved to be compatible with an aqueous iodine environment. In addition to the specimens exposed to aqueous iodine, a stainless steel specimen (unspecified alloy) was exposed to moist microbial check valve resin and air for a comparable period. This environment allowed contact of the metal to the resin as well as to the iodine vapor. Since the particular stainless steel alloy was not known, energy dispersive spectroscopy was used to determine that this alloy was stainless steel 301. The intergranular corrosion found on the specimen was limited to the first grain boundary layer.
Countering Weapons of Mass Destruction (CWMD) recognizes that threats in the cyberspace domain continue to grow, which requires CWMD devices and supporting systems to be both cybersecure (ability to protect or defend from cyber-attacks) and resilient (ability to maintain required capability in the face of adversity) to cyber threats. The CWMD cybersecurity characterization approach in this document supports existing cyber resilience activities within the Acquisition Lifecycle Framework. Similarly, this process supports existing Department of Homeland Security Cyber Resilience Test and Evaluation activities, which consist of iterative processes, starting at the initiation of system acquisition and continuing throughout the entire device and system life cycle. Cyber resilience is the ability of an information system to continue to operate while under attack, even if in a degraded or debilitated state,1 and to rapidly recover operational capabilities for essential functions after a successful attack.2 The goal of the security characterization task for CWMD is to support the development of a CBRN device-dependent profile that aligns with device network capabilities and maps to recommended security controls to create a characterization security profile impact levels. The impact levels for CWMD devices should be characterized as Low (L), Moderate (M), High (H) to align with the low, moderate, high control baselines. To estimate the impact levels, the device’s security-related attributes are translated into the security objectives: Confidentiality (C), Integrity (I), and Availability (A), known as the CIA triad. The potential impact for each device can be L, M, H, for devices that connect and transmit different types of data and may have different impact levels. National Institute of Standards and Technology Federal Information Processing Standards Publication 199 states, “the potential impact values assigned to the respective security objectives shall be the highest value from among those security categories that have been determined for each type of information resident on the information system.”3 As CWMD is determining the cybersecurity impact levels of CBRN devices based on network connections and data transfers, the impact levels are aligned with the associated attributes of network connections and communications. For example, if the device system is connected to a wireless network and transmits different data types based on the confidentiality of the data, the highest impact value for each security objective should represent the device’s CIA impact level. This document is intended to be used by test managers, test team, and program managers.
An integrated circuit system having an integrated circuit (IC) component which is able to have its functionality destroyed upon receiving a command signal. The system may involve a substrate with the IC component being supported on the substrate. A module may be disposed in proximity to the IC component. The module may have a cavity and a dissolving compound in a solid form disposed in the cavity. A heater component may be configured to heat the dissolving compound to a point of sublimation where the dissolving compound changes from a solid to a gaseous dissolving compound. A triggering mechanism may be used for initiating a dissolution process whereby the gaseous dissolving compound is allowed to attack the IC component and destroy a functionality of the IC component.
The stability and receptivity of three-dimensional supersonic boundary layers over a 7deg sharp tipped straight cone at an angle of attack of 4.2deg is numerically investigated at a free stream Mach number of 3.5 and at two high Reynolds numbers, 0.25 and 0.50x10(exp 6)/inch. The generation and evolution of stationary crossflow vortices are also investigated by performing simulations with three-dimensional roughness elements located on the surface of the cone. The flow fields with and without the roughness elements are obtained by solving the full Navier-Stokes equations in cylindrical coordinates using the fifth-order accurate weighted essentially non-oscillatory (WENO) scheme for spatial discretization and using the third-order total-variation-diminishing (TVD) Runge-Kutta scheme for temporal integration. Stability computations reveal that the azimuthal wavenumbers are in the range of m approx. 25-50 for the most amplified traveling disturbances and in the range of m approx. 40-70 for the stationary disturbances. The N-Factor computations predicted that transition would occur further forward in the middle of the cone compared to the transition fronts near the windward and the leeward planes. The simulations revealed that the crossflow vortices originating from the nose region propagate towards the leeward plane. No perturbations were observed in the lower part of the cone.
This report summarizes the work performed under the project project Next-Generation Algorithms for Assessing Infrastructure Vulnerability and Optimizing System Resilience. The goal of the project was to improve mathematical programming-based optimization technology for infrastructure protection. In general, the owner of a network wishes to design a network a network that can perform well when certain transportation channels are inhibited (e.g. destroyed) by an adversary. These are typically bi-level problems where the owner designs a system, an adversary optimally attacks it, and then the owner can recover by optimally using the remaining network. This project funded three years of Deon Burchett's graduate research. Deon's graduate advisor, Professor Jean-Philippe Richard, and his Sandia advisors, Richard Chen and Cynthia Phillips, supported Deon on other funds or volunteer time. This report is, therefore. essentially a replication of the Ph.D. dissertation it funded in a format required for project documentation. The thesis had some general polyhedral research. This is the study of the structure of the feasible region of mathematical programs, such as integer programs. For example, an integer program optimizes a linear objective function subject to linear constraints, and (nonlinear) integrality constraints on the variables. The feasible region without the integrality constraints is a convex polygon. Careful study of additional valid constraints can significantly improve computational performance. Here is the abstract from the dissertation: We perform a polyhedral study of a multi-commodity generalization of variable upper bound flow models. In particular, we establish some relations between facets of single- and multi- commodity models. We then introduce a new family of inequalities, which generalizes traditional flow cover inequalities to the multi-commodity context. We present encouraging numerical results. We also consider the directed edge-failure resilient network design problem (DRNDP). This problem entails the design of a directed multi-commodity flow network that is capable of fulfilling a specified percentage of demands in the event that any G arcs are destroyed, where G is a constant parameter. We present a formulation of DRNDP and solve it in a branch-column-cut framework. We present computational results.
This paper presents the development of flexible wings, flapping mechanism, and integrated electronic control system (ECS) to emulate the bat wing flapping for the ongoing micro air vehicle (MAV) research. Three bat species having dimensions close to the design requirement of MAV, namely, Mormopterus Planiceps, Nytophilus Geoffroyi, and Scotorepens Balstoni were selected, and the average of their physical dimensions was chosen. The commercially available titanium alloy, Ti ± 6Al ± 4V, was used for the wing frame, and the membrane was made of latex. A four-bar slider-crank mechanism was designed and fabricated to facilitate the wing flapping; ECS controlled the flapping frequency in the real-time mode. The system was tested in open air wind tunnel at frequency6 Hz, angle of attack (AOA) 0–50°, and velocity range 2–7 m s{sup −1}. The experimental flapping angle which is compared with the theoretical flapping angle was obtained from the analytical kinematic model. The mean lift and drag coefficients were also measured and the results were found to be excellent. Compared to the manual control and measurement of flapping frequency, the proposed ECS demonstrates efficient control and accurate measurement. Moreover, the tedious procedure involved in the repeated calibrations for the manual system is totally eliminated by ECS.
In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator O i of Sensor Network S i to correctly determine the number of active sensors in Network Si. Such a problem is challenging in collaborating sensor networks where other sensor networks, despite showing an intent to collaborate, may not be completely trustworthy and could compromise the authentication process. We propose two authentication protocols to address this problem. Our protocols rely on Physically Unclonable Functions, which are a hardware based authentication primitive exploiting inherent randomness in circuit fabrication. Our protocols are light-weight, energy efficient, and highly secure against a number of attacks. To the best of our knowledge, ours is the first to addresses a practical security problem in collaborating sensor networks.
The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.
Boundary layer ingesting (BLI) propulsion systems are one of the many technologies currently under investigation within the aerospace community to meet NASA's Advanced Air Transport Technology project goal of a sustainable future in aviation. To that end, an experimental campaign was conducted in the National Transonic Facility (NTF) wind tunnel to study the propulsion-airframe integration effects of the Boundary Layer Ingesting Tailcone System installed in the aft portion of a 2.7% scale design of the NASA Common Research Model (CRM). This test was accompanied by a numerical simulation effort using the Launch, Ascent, and Vehicle Aerodynamics (LAVA) curvilinear solver to validate the applicability of current best-practice Reynolds-Averaged Navier-Stokes (RANS) models in accurately predicting the relevant flow physics in free-air. A total of 205 steady RANS simulations were performed using LAVA, covering the range of conditions present in the NTF test matrix. Flow conditions ranged from 5- to 15-million Reynolds number, Mach numbers of 0.75, 0.80 and 0.85, and angles of attack between -3 and 4 degrees. Four different mass-flow plugs were also tested to assess propulsor operating condition effects. Sensitivity to these flow conditions is analyzed in detail, especially in terms of the nacelle flow distortion which was the main subject of the study. Aerodynamic load coefficients, aft body boundary layer measurements and fuselage pressure tap results are also discussed, providing a wide range of validation results from this experimental campaign. This validation effort shows that current best-practices using RANS models within the LAVA curvilinear solver flow solver are well suited for predicting the inlet flow distortion characteristics of novel aircraft configurations employing BLI at the aft end of the fuselage. This talk will cover the combined experimental and numerical efforts that resulted from this BLI-focused investigation.
To meet the increasing demand for electricity and to have a more reliable and resilient electric grid against conventional and extreme events, grid modernization is more crucial now than ever before. This will require the development and deployment of devices that provide advanced communication capabilities. The overall efficiency, reliability, and resilience of the smart grid will be inextricably linked to the exchange of information between these devices. Unfortunately, the increased information flow will increase the potential attack surface and introduce new vulnerabilities. While a smarter grid will depend critically on information flow, these benefits will be accrued only if that information can be protected. Nowadays, information is secured in smart grids primarily through cryptography. However, with the increasing number of sophisticated attacks as well as the increasing computational power, the security of the “classical” cryptographic algorithms is threatened. Quantum information science offers solutions to this problem, specifically quantum key distribution (QKD), which provides a means for the generation and secure distribution of symmetric cryptographic keys. The security of QKD stems ultimately from the very nature of quantum physics. In this paper, we investigate the applicability of QKD to the various smart grid sectors and specific use cases. We have identified 18 smart grid use cases of interest for QKD suitability together with 7 QKD factors used for the assessment of the various use cases. For each use case, the impact to security of the loss of confidentiality, integrity, and/or availability is specified. In addition, the suitability of QKD is assessed for each use case with respect to multiple factors.
Abstract A multi-physics material model is presented to describe the effects of temperature, oxygen, and humidity on the constitutive response of cross-linked polymers. The effect of hygrothermal damage on the mechanical integrity of the polymer matrix can be considered as the result of damage accumulation of two independent aging mechanism namely, i) thermo-oxidative, and ii) hydrolytic aging. In order to capture the mutual effects of thermo-oxidative and hydrolytic aging, an assumption has been made that each of the aging phenomenon can be superposed to each other. In fact, each of them works independently and as a result, they can compete with each other. Utilizing the theory of network decomposition, all phenomena and their correlation were modeled and thus, the strain energy function of the polymer matrix is written with respect to four independent mechanisms, i) the shrinking original matrix that has neither been attacked by water nor oxygen, ii) conversion of the first network to two new network due to the reduction and formation of cross-links, and iii) energy loss from network degradation due to attack of the water molecules to polymer active agents. Moreover, the proposed model is micro-mechanically based and is mainly relevant on thin samples due to our underlying assumption of homogeneous diffusion of oxygen and water throughout the matrix. The model has been validated against extensive data-sets obtained from experiments we specifically designed for concept validation.
Boundary-layer ingesting (BLI) propulsion systems are one of the many technologies currently under investigation within the aerospace community to meet NASA’s Advanced Air Transport Technology project goal of a sustainable future in aviation. To that end, an experimental campaign was conducted in the National Transonic Facility (NTF) to study the propulsion-airframe integration effects of the Boundary-Layer Ingesting Tailcone System installed in the aft portion of a 2.7% scale design of the NASA Common Research Model (CRM). This test was accompanied by a numerical simulation effort using the Launch, Ascent, and Vehicle Aerodynamics (LAVA) solver, to validate the applicability of current best-practice Reynolds-averaged Navier Stokes (RANS) models in accurately predicting the relevant flow-physics in free-air. A total of 205 steady RANS simulations were performed using LAVA, covering the range of conditions present in the NTF test matrix. Flow conditions ranged from 5- to 15-million Reynolds number, Mach numbers of 0.75, 0.80 and 0.85, and angles-of-attack between –3° and 4°. Four different mass-flow plugs were also tested to assess propulsor operating condition effects. Sensitivity to these flow conditions are analyzed in detail, especially in terms of the nacelle flow distortion which was the main subject of the study. Aerodynamic load coefficients, aftbody boundary-layer measurements and fuselage pressure tap results are also discussed, providing a wide range of validation results from this experimental campaign. This validation effort shows that current best-practices using RANS models within the LAVA solver flow solver are well suited for predicting the inlet flow distortion characteristics of novel aircraft configurations employing BLI at the aft end of the fuselage.