Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (5735)
- Physical Sciences and Mathematics (2950)
- Aerospace Engineering (1674)
- Electrical and Computer Engineering (1344)
- Operations Research, Systems Engineering and Industrial Engineering (1247)
-
- Computer Sciences (1236)
- Business (994)
- Physics (919)
- Operational Research (610)
- Signal Processing (459)
- Civil and Environmental Engineering (422)
- Computer Engineering (414)
- Aviation (353)
- Electrical and Electronics (351)
- Social and Behavioral Sciences (349)
- Operations and Supply Chain Management (346)
- Materials Science and Engineering (335)
- Optics (330)
- Oceanography and Atmospheric Sciences and Meteorology (279)
- Navigation, Guidance, Control and Dynamics (252)
- Other Operations Research, Systems Engineering and Industrial Engineering (233)
- Human Resources Management (232)
- Systems Engineering (229)
- Atomic, Molecular and Optical Physics (198)
- Electromagnetics and Photonics (195)
- Aerodynamics and Fluid Mechanics (188)
- Environmental Sciences (188)
- Environmental Engineering (185)
- Nuclear Engineering (180)
- Applied Mathematics (178)
- Keyword
-
- #antcenter (380)
- #csra (134)
- Machine learning (93)
- Decision making (89)
- Algorithms (75)
-
- Global Positioning System (75)
- Image processing (73)
- Kalman filtering (65)
- Optimization (64)
- #afcec (62)
- Computer networks--Security measures (62)
- Drone aircraft (59)
- Computer security (57)
- Target acquisition (57)
- Neural networks (Computer science) (54)
- Software engineering (54)
- Additive manufacturing (52)
- Remote sensing (49)
- Flight control (48)
- Microelectromechanical systems (45)
- Computer vision (44)
- Artificial satellites (43)
- Decision support systems (43)
- #ctisr (42)
- Adaptive optics (42)
- Composite materials (42)
- Neural networks (41)
- Simulation (41)
- Wireless communication systems (41)
- Scheduling (40)
- Publication Year
- Publication
- Publication Type
- File Type
Articles 1081 - 1110 of 8791
Full-Text Articles in Entire DC Network
Reinvigorating A Technical Countering Weapons Of Mass Destruction Distance Learning Graduate Certificate Program, James C. Petrosky, Gaiven Varshney, Jeremy Slagley, Sara Shaghaghi
Reinvigorating A Technical Countering Weapons Of Mass Destruction Distance Learning Graduate Certificate Program, James C. Petrosky, Gaiven Varshney, Jeremy Slagley, Sara Shaghaghi
Faculty Publications
Current Countering Weapons of Mass Destruction (CWMD) demands can be divided broadly into policy and science. The science of chemical, biological, and radiological/nuclear weapons informs the limits of development, production, employment, operation, detection, risk characterization, human and material protection, and medical intervention. In short, the science of weapons of mass destruction (WMD) should precede and inform the development of policy. It is to this end that the Air Force Institute of Technology (AFIT) CWMD program was re-established, providing a technical educational option for practitioners to understand the science behind a very technically challenging subject.
Cognition-Enhanced Machine Learning For Better Predictions With Limited Data, Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua W. Wood, Michael Krusmark, Tiffany Jastrzembski, Christopher W. Myers
Cognition-Enhanced Machine Learning For Better Predictions With Limited Data, Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua W. Wood, Michael Krusmark, Tiffany Jastrzembski, Christopher W. Myers
Faculty Publications
The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields’ methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based on learning histories are central to developing effective, personalized learning tools. Here, we show how a state-of-the-art ML model can …
Characterization Of Anisotropic Materials Using Scattered Field Measurements, Hirsch M. Chizever
Characterization Of Anisotropic Materials Using Scattered Field Measurements, Hirsch M. Chizever
Theses and Dissertations
This research uses monostatic far-zone scattered field measurements to estimate the permittivity of biaxial materials at X-Band. Utilizing Radar Cross Section (RCS) measurement techniques, this effort examines the efficacy of whole-sample TEM illumination in the estimation of anisotropic permittivity, in contrast with traditional subsample illumination methods. The research examines the impact that dielectric supports have on measurement error and uncertainty in permittivity estimates. Following an incremental approach, the research first demonstrates successful estimation of permittivity for isotropic spheres followed by a Teflon isotropic cube. Finally, the method is applied to uniaxial and biaxial cubes whose anisotropic permittivity is validated through …
Equichordal Tight Fusion Frames And Biangular Orthopartitionable Tight Frames, Benjamin R. Mayo
Equichordal Tight Fusion Frames And Biangular Orthopartitionable Tight Frames, Benjamin R. Mayo
Theses and Dissertations
An equichordal tight fusion frame (ECTFF) is a sequence of equidimensional subspaces of a Euclidean space that achieves equality in Conway, Hardin and Sloane's simplex bound, and so is a type of optimal Grassmannian code. In the special case where its subspaces have dimension one, an ECTFF corresponds to an equiangular tight frame (ETF); such frames have minimal coherence and so are useful for compressed sensing. More generally, an ECTFF will yield a frame with minimal block coherence when its subspaces are pairwise isoclinic, namely when it is an equi-isoclinic tight fusion frame (EITFF). In this dissertation, we generalize the …
Evaluating Testing Procedures For Openflow Controller Network Re-Provisioning Time, Steven J. Jensen
Evaluating Testing Procedures For Openflow Controller Network Re-Provisioning Time, Steven J. Jensen
Theses and Dissertations
Software-Defined Networking promises several advantages over traditional networking architectures, but has seen little adoption. Recently codified controller evaluation methodologies have seen little validation without strong statistical analysis of the results. The research developed an environment testing implementing a published Network Re-provisioning Time methodology to evaluate five OpenFlow controllers. The methodology is strong with required parameters but had issues with some edge cases. Further refinement and adding a convergence metric may close the gaps.
Analysis Of Space To Ground Ladar Performance With Non-Traditional Optics, Prayant P.S. Hanjra
Analysis Of Space To Ground Ladar Performance With Non-Traditional Optics, Prayant P.S. Hanjra
Theses and Dissertations
Two major obstacles to space-based LADAR systems are low power returns from targets and limitations on size and weight for transporting large optics into orbit. Signals incur significant losses during roundtrip propagation through the atmosphere and from diffuse scattering off of targets. Models, such as the Laser Environmental Effects Definition and Reference (LEEDR) simulator and High Energy Laser End to End Operational Simulation (HELEEOS) can predict these losses due to the atmosphere and optical components for a variety of atmospheric and environmental conditions across the globe. A transmissometer is used to validate these models. These losses are used to determine …
Relationship Between Solar Energetic Particle He/H Abundance Ratios And Properties Of Flares And Cmes, Christopher R. Davidson
Relationship Between Solar Energetic Particle He/H Abundance Ratios And Properties Of Flares And Cmes, Christopher R. Davidson
Theses and Dissertations
Previous studies have investigated the He/H elemental abundance ratios of Solar Energetic Particle (SEP) Events of energies above 4 MeV. Also, studies have investigated the correlations between SEPs, Coronal Mass Ejections (CME), and Solar Flares. This work finds the correlations between the >4 MeV He/H abundance ratios and the solar parameters from the SEP, CME, and solar flare associated with the abundance increases. 43 SEP events located at solar west longitude are analyzed to find the correlation coefficients. Highly significant correlation was found between the He/H abundance ratios and the following parameters: solar flare flux, solar flare fluence, CME linear …
Instabilities Of Overturned Traveling Waves, Tyler B. Pierce
Instabilities Of Overturned Traveling Waves, Tyler B. Pierce
Theses and Dissertations
The instabilities of overturned traveling waves are determined by the use of spectral methods. Two separate numerical methods, Spectral Stability Analysis and Dynamic Stability Analysis, are used to assess the instabilities of branches of waves solved from conformally-mapped Euler equations. The branches of waves with Bond number less than two were found to be spectrally stable to super-harmonic perturbations. The branches of waves with Bond number in [2,3) had some waves that were stable and some that were unstable. All overturned waves with Bond number greater than or equal to two were unstable.
Determining Physical Characteristics Through Information Leakage In 802.11ac Beamforming, Albert D. Taglieri
Determining Physical Characteristics Through Information Leakage In 802.11ac Beamforming, Albert D. Taglieri
Theses and Dissertations
The risk of information leakage in 802.11ac allows an eavesdropper to monitor wireless traffic and correlate physical locations between devices, as well as environment changes such as the motion of a person. Previous pattern-analysis mitigation methods, which used nonexistent devices to fool an eavesdropper, are not effective in an 802.11ac network, because devices on the network can be correlated to their physical location, which a nonexistent device does not have. Further, additional information about motion in the target environment can be observed and analyzed, providing a new potential for pattern analysis and sensing. 802.11ac makes it possible to plug in …
Advancing Proper Dataset Partitioning And Classification Of Visual Search And The Vigilance Decrement Using Eeg Deep Learning Algorithms, Alexander J. Kamrud
Advancing Proper Dataset Partitioning And Classification Of Visual Search And The Vigilance Decrement Using Eeg Deep Learning Algorithms, Alexander J. Kamrud
Theses and Dissertations
Electroencephalography (EEG) classification of visual search and vigilance tasks has vast potential in its benefits. In future human-machine teaming systems, EEG could act as the tool for operator state assessment, enabling AI teammates to know when to assist the operator in these tasks, with the potential to lead to increased safety of operations, better training systems for our operators, and improved operational effectiveness. This research investigates deep learning methods which utilize EEG signals to classify the efficiency of an operator's search and to classify whether an operator is in a decrement during a vigilance type task, and investigates performing these …
Profiling Atmospheric Turbulence Using A Dynamically Ranged Rayleigh Beacon System, Steven M. Zuraski
Profiling Atmospheric Turbulence Using A Dynamically Ranged Rayleigh Beacon System, Steven M. Zuraski
Theses and Dissertations
The effect of turbulence on a long range imaging system manifest as an image blur effect usually quantified by the phase distortions present in a system. The blurring effect is conceivably understood on the basis of measured strength of atmospheric turbulence profiled within the propagation volume. One method for obtaining a turbulence strength profile is by use of a dynamically ranged Rayleigh beacon system that exploits strategically varied beacon ranges along the propagation path, effectively deducing estimates of specific path segment contributions of the blurring aberrations affecting an optical imaging system. A system utilizing this technique has been designed, and …
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Theses and Dissertations
Clustering weather data is a valuable endeavor in multiple respects. The results can be used in various ways within a larger weather prediction framework or could simply serve as an analytical tool for characterizing climatic differences of a particular region of interest. This research proposes a methodology for clustering geographic locations based on the similarity in shape of their temperature time series over a long time horizon of approximately 11 months. To this end an emerging and powerful class of clustering techniques that leverages deep learning, called deep representation clustering (DRC), are utilized. Moreover, a time series specific DRC algorithm …
Physically Unclonable Characteristics For Verification Of Transmon-Based Quantum Computers, Leleia A. Hsia
Physically Unclonable Characteristics For Verification Of Transmon-Based Quantum Computers, Leleia A. Hsia
Theses and Dissertations
Future national security can be strengthened by verifying and securing the quantum computing supply chain. This dissertation proposes physically unclonable characteristics (PUCs), a method of quantum hardware verification inspired by classical physically unclonable functions, for future application to quantum processors implemented with transmon qubits. Qualitative and quantitative analysis is provided on the development of PUCs, including identifying qubit characteristics and qubit discrimination methods suitable for PUCs. Characteristics tested on IBM Quantum services include T1 and T2 coherence times, single-qubit and multi-qubit gate error rates, readout error rates, quantum process tomography metrics, and random benchmarking metrics. Results show that non-parametric qubit …
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Theses and Dissertations
This research considers the problem of an intruder attempting to traverse a defender's territory in which the defender locates and employs disparate sets of resources to lower the probability of a successful intrusion. The research is conducted in the form of three related research components. The first component examines the problem in which the defender subdivides their territory into spatial stages and knows the plan of intrusion. Alternative resource-probability modeling techniques as well as variable bounding techniques are examined to improve the convergence of global solvers for this nonlinear, nonconvex optimization problem. The second component studies a similar problem but …
Improved Out-Of-Plane Brdf Measurement And Modeling, Todd V. Small
Improved Out-Of-Plane Brdf Measurement And Modeling, Todd V. Small
Theses and Dissertations
The bi-directional reflectance distribution function (BRDF) describes the directional (spatial) nature of light’s reflectance from a material surface. When incident light of a particular wavelength strikes a material surface from a particular direction, portions of that incident light will be reflected into various directions in various amounts, depending on the material’s surface characteristics. Historically, the vast majority of BRDF measurement and modeling research has focused on reflection within the plane-of incidence (in-plane) and dealt primarily with simplified isotropic BRDFs. Remote sensing applications, such as satellite light curve analysis, typically rely on closed-form microfacet models for efficiency. There are many factors, …
Characterizing Convolutional Neural Network Early-Learning And Accelerating Non-Adaptive, First-Order Methods With Localized Lagrangian Restricted Memory Level Bundling, Benjamin O. Morris
Characterizing Convolutional Neural Network Early-Learning And Accelerating Non-Adaptive, First-Order Methods With Localized Lagrangian Restricted Memory Level Bundling, Benjamin O. Morris
Theses and Dissertations
This dissertation studies the underlying optimization problem encountered during the early-learning stages of convolutional neural networks and introduces a training algorithm competitive with existing state-of-the-art methods. First, a Design of Experiments method is introduced to systematically measure empirical second-order Lipschitz upper bound and region size estimates for local regions of convolutional neural network loss surfaces experienced during the early-learning stages. This method demonstrates that architecture choices can significantly impact the local loss surfaces traversed during training. Next, a Design of Experiments method is used to study the effects convolutional neural network architecture hyperparameters have on different optimization routines' abilities to …
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
Theses and Dissertations
A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …
Development And Verification Of Extreme Space Weather Phenomena Models, Sophia G. Schwalbe
Development And Verification Of Extreme Space Weather Phenomena Models, Sophia G. Schwalbe
Theses and Dissertations
A range of 14 M-class flares from 1 June 2015 to 27 September 2016 were analyzed to find significant trends in electron frequency profile modeling using the GLobal airglOW (GLOW) model and radar parameters using a ray tracing algorithm developed by the Air Force Research Laboratory. GLOW was run for all the flares using three different solar spectrum schemes and an average of the three: the Hinteregger method, EUV flux model for aeronomic calculations (EUVAC), and a rebinned Flare Irradiance Spectrum Model (FISM) result. Comparing data for the E-layer where GLOW is most accurate, it was determined that GLOW using …
Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom
Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom
Theses and Dissertations
Space launch operations at Kennedy Space Center and Cape Canaveral Space Force Station (KSC/CCSFS) are complicated by unique requirements for near-real time determination of risk from lightning. Lightning forecast weather sensor networks produce data that are noisy, high volume, and high frequency time series for which traditional forecasting methods are often ill-suited. Current approaches result in significant residual uncertainties and consequentially may result in forecasting operational policies that are excessively conservative or inefficient. This work proposes a new methodology of wavelet-enabled semiparametric modeling to develop accurate and timely forecasts robust against chaotic functional data. Wavelets methods are first used to …
Collaborative All-Source Navigation With Integrity, Jonathon S. Gipson
Collaborative All-Source Navigation With Integrity, Jonathon S. Gipson
Theses and Dissertations
The novel ARMAS-SOM framework fuses collaborative all-source sensor information in a resilient manner with fault detection, exclusion, and integrity solutions recognizable to a GNSS user. This framework uses a multi-filter residual monitoring approach for fault detection and exclusion and is augmented with an additional "observability" EKF sub-layer for resilience. We monitor the a posteriori state covariances in this sub-layer to provide intrinsic awareness when navigation state observability assumptions required for integrity are in danger. This is used to selectively augment the framework with offboard information to preserve resilience. By maintaining split parallel collaborative and proprioceptive estimation instances and employing a …
Interdependent Infrastructure Recovery Using Multilayered Networks And Optimization, Brigham A. Moore
Interdependent Infrastructure Recovery Using Multilayered Networks And Optimization, Brigham A. Moore
Theses and Dissertations
Interdependent infrastructure recovery modeling and simulation are complicated due to various interdependent connections and complexities. Current efforts have identified both operational and restoration interdependency subtypes and coupling strategies that have not been integrated into one comprehensive model. This research presents a model which simultaneously integrates nine interdependency subtypes and four coupling strategies in a multi-objective format to provide the most tailorable and comprehensive network-based recovery model available. This research also created a defense-centric interdependent infrastructure database by modifying the existing CLARC database. This research then addressed assumptions regarding recovery work management in order to address the impact of work crew …
Visual Navigation And Control For Spacecraft Proximity Operations With Unknown Targets, Wyatt J. Harris
Visual Navigation And Control For Spacecraft Proximity Operations With Unknown Targets, Wyatt J. Harris
Theses and Dissertations
Many current and future spacecraft missions must conduct rendezvous and proximity operations (RPO) with resident space objects (RSOs). An important subset of spacecraft RPO that is yet to be demonstrated on-orbit involves final approach maneuvers with respect to RSOs where no information (such as geometry, inertia, relative velocity, etc.) is known about the target a priori, and no information is actively provided by the target during maneuvering. Such operation with respect to ‘unknown’ targets represents an important possible mission set for Department of Defense spacecraft and is the subject of this research. Two visual servoing frameworks capable of autonomously controlling …
Stochastic Satellite Air Drag With The Ballistic Coefficient As A Random Variable, Everett B. Palmer Iv
Stochastic Satellite Air Drag With The Ballistic Coefficient As A Random Variable, Everett B. Palmer Iv
Theses and Dissertations
The drag acceleration caused by the Earth's atmosphere is a significant cause of prediction uncertainty for low Earth orbit satellites. Most existing research has focused on improving deterministic atmospheric density predictions or on density as a random variable. This research investigates a new paradigm and focuses on modeling the uncertainty caused by air drag using the ballistic coefficient, a component of air drag that is independent of the model used to predict atmospheric density. Time series of ballistic coefficient values were calculated and analyzed as random processes. These random processes were then used as the foundation of a stochastic satellite …
A Real-Time Algorithm To Achieve Precise Coordinated Arrival Times In A Time-Variant Environment, Shawn S. Stephens
A Real-Time Algorithm To Achieve Precise Coordinated Arrival Times In A Time-Variant Environment, Shawn S. Stephens
Theses and Dissertations
The coordinated arrival time problem seeks to control a vehicle's trajectory to achieve some pre-defined final state at a desired arrival time. The persistent monitoring problem is a type of coordinated arrival problem where a stationary or moving ground target must be constantly observed by a group of aircraft. This research simplifies the problem to overfly the target at specific time intervals relative to the other aircraft in the group while increasing the difficulty of the problem by considering aircraft traveling at vastly different airspeeds. The result of this research is a real time guidance algorithm which accurately guides a …
Optimal Incorporation Of Non-Traditional Sensors Into The Space Domain Awareness Architecture, Albert R. Vasso
Optimal Incorporation Of Non-Traditional Sensors Into The Space Domain Awareness Architecture, Albert R. Vasso
Theses and Dissertations
The United States Government is the world’s de facto provider of space object cataloging data, but is challenged to maintain pace in an increasingly complex space environment. This work advances a multi-disciplinary approach to better understand and evaluate an underexplored solution recommended by national policy, in which current collection capabilities are augmented with non-traditional sensors. System architecting and literature identify likely needs, performance measures, and contributors to a conceptualized Augmented Network. Multiple hypothetical telescope architectures are modeled and simulated on four separate days throughout the year, then evaluated against performance measures and constraints using optimization. Decision analysis and Pareto optimality …
Applying Model-Based Systems Engineering And Fidelity Quantification To Support Fair Fight In A Distributed Simulation System, Nathaniel Erbe, David Lemmer
Applying Model-Based Systems Engineering And Fidelity Quantification To Support Fair Fight In A Distributed Simulation System, Nathaniel Erbe, David Lemmer
Theses and Dissertations
Current 5th and 6th generation fighter aircraft capabilities, and the DoD's push towards digital engineering have created an environment in which simulated testing using live, virtual, and constructive assets has increasing utility. These simulations need to be credible in the eyes of the stakeholders, which for distributed simulation systems includes establishing fair fight between simulation services. Fair fight is when multiple simulations interoperate without generating one-sided systematic advantages. Issues that impede fair fight can be categorized into interoperability issues at the simulations implementation level and incompatible representations of reality between underlying models. This research used model-based systems engineering to generate …
Evaluation Of Additively Manufactured Lattices Under High Strain Rate Impact, Derek G. Spear
Evaluation Of Additively Manufactured Lattices Under High Strain Rate Impact, Derek G. Spear
Theses and Dissertations
Several additively manufactured lattice designs and configurations were evaluated under compression loads under various strain rates from quasi-static to highly dynamic. These experiments examined how the mechanical behavior of the lattice changed based on the lattice design properties and the applied strain rates. The modulus of elasticity, yield strength, plateau stress, and toughness were observed to decrease with an increase in strain rate, revealing that the lattice designs exhibit a negative strain rate sensitivity. A new lattice flow stress model was developed to account for the mechanical response of the lattice and was incorporated into a computational model for simulation. …
Improvements To Emissive Plume And Shock Wave Diagnostics And Interpretation During Pulsed Laser Ablation Of Graphite, Timothy I. Calver
Improvements To Emissive Plume And Shock Wave Diagnostics And Interpretation During Pulsed Laser Ablation Of Graphite, Timothy I. Calver
Theses and Dissertations
This dissertation covers nanosecond pulsed laser ablation of graphite for 4-5.7 J/cm2 fluences with 248 nm and 532 nm lasers in 1-180 Torr helium, argon, nitrogen, air, and mixed gas. Three experiments were performed to improve the interpretation of common diagnostics used to characterize pulsed laser ablation, find simple but universal scaling relationships for comparing dynamics across different materials and ablation conditions, and provide a systematic analysis of graphite emissive plume and shock wave dynamics. A scaling of the Sedov-Taylor energy ratio was developed and validated for a range of studies despite differences in wavelength, pulse duration, fluence, and …
Requirements Analysis And Architecture For An Operational Study Of Fatigue In Usaf Mobility Aircrew, Jonathan F. Mecham
Requirements Analysis And Architecture For An Operational Study Of Fatigue In Usaf Mobility Aircrew, Jonathan F. Mecham
Theses and Dissertations
Aircrew fatigue in flight operations is a known hazard that has driven the creation of fatigue-reducing regulation and fatigue risk management systems industry wide. In addition, biomathematical models have been created and tested to forecast the effectiveness of aircrew under conditions of time-zone shifts and long duty days. However, limited operational studies exist to validate these models or to help understand how individual factors can affect them. Operational studies have a variety of limitations that make gathering typical data regarding fatigue or sleep difficult. This research takes systems requirement analysis approach to design a study that measures effects of circadian …
Performance Improvement Through Better Understanding Of Supply Chain Resilience, Amanda L. Femano
Performance Improvement Through Better Understanding Of Supply Chain Resilience, Amanda L. Femano
Theses and Dissertations
Businesses operate every day in a disruptive environment. Supply and demand uncertainty, natural disasters, global pandemics, and mishaps can all cause chaos to a supply chain’s flow. It is impossible to predict every disruption a supply chain may encounter. The best an organization can do to protect network performance is to build resilience in the supply chain and life-blood of its operations. Ensuring that a supply chain has the proper built-in mechanisms to resist and recover from disruptions is referred to as Supply Chain Resilience (SCR). While it is generally agreed that SCR can be improved through the implementation of …