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Development and Analysis of Military Cost-Imposing Actions
No full textWe present a systematic approach to identify potential military cost-imposing actions and possible adversary responses. The cost imposition is evaluated in terms of budgets and resources over an extended period of time. Hence, the decision space for cost-imposing actions and responses are force mix choices and adopting new strategies that affect a potential future conflict. The cost imposer takes an initial action, such as deploying an advanced system with new technology, intended to cause the targeted opponent to expend more resources in countering this initiative. We estimate the extent of the adversary\u27s response to maintain their overall effectiveness in the projected military campaign. We evaluate the ratios of costs for the adversary responses that are sufficient to achieve the original effectiveness over the cost of military actions of imposition; these ratios are the relative cost incurred. Ratios greater than 1 represent viable cost-imposing actions, with higher ratios being better for the cost imposer
Magnetohydrodynamic mixed convection of nanofluid flow in a split lid driven cavity using finite element method
No full textExcerpt: A computational study on the effect of magnetohydrodynamic mixed convection of nanofluid flow in a square split lid driven cavity with a block placed near the bottom wall is undertaken. Two different nanoparticles gold and alumina are considered for the study. The observations for the study are obtained by solving the non-dimensionalized governing equations by Finite Element Method with variational approach as accessible with the FreeFEM++ software
Predicting Broadband Powerline Communications Performance on Microgrid Networks
No full textExcerpt: The distributed-element transmission line model is modified to account for proximity effects in multiconductor cables and frequency dependent dielectric behavior providing an accurate prediction of channel attenuation at broadband power line communication frequencies (1-100 MHz). The modified model is verified with scattering parameter measurements and then used as a building block for complex microgrid network modelling
Investigation of near-rectilinear halo orbit search and rescue using staging L\u3csub\u3e1\u3c/sub\u3e / L\u3csub\u3e2\u3c/sub\u3e Lyapunov and distant retrograde orbit families
No full textExcerpt: Cislunar space is a region of growing interest with nations investing resources to cultivate long presence habitations on the lunar surface. With this increased attention and expansion of missions, both crewed and uncrewed, the likelihood of a mishap or a spacecraft becoming impaired and unable to continue its mission will also increase. The present research adds to the field of cislunar mission operations and trajectory analysis by investigating search and rescue (SAR) operations via rendezvous and proximity operations (RPO) with an impaired notional spacecraft located in a Near-Rectlinear Halo Orbit (NRHO). This research compares the response times of rescuer spacecraft located in sample distant retrograde orbits (DROs) and L1/L2 Lyapunov orbits for the timely far rendezvous with the impaired spacecraft located in the NRHO
Malware Detection and Signature Propagation: A Study on Anti-Virus Platforms
Get PDFThe early detection of malware across DoD networks is paramount when considering which AV engine to employ. This study explores malware detection latency across various AV providers over a 30-day period using VirusTotal’s platform. The analysis reveals an initial surge in detections, reaching approximately 60% within 24 hours. From days 3 to 20, detections steadily increase by 1-3 instances per day, peaking at 74% on the 20th day, followed by a slight decline. The research also highlights a significant difference in false positive rates between packed and non-packed non-malicious samples, emphasizing the impact of packing on AV engine scans. While obfuscation methods show limited impact on detection rates, they reveal distinct variations in false positives among different protection techniques. Examination of individual AV engines suggests potential file signature sharing, hinting at collaborative detection behaviors among certain providers. Overall, this research underscores detection timelines, false positives in packed non-malicious files, and nuanced behaviors of AV engines
Reconstruction of Radar Range Profiles Using Dropped Channel Polarimetric Compressive Sensing
Get PDFThis thesis documents the design, construction and testing of a bench-top level measurement system and verifies previously established Dropped Channel Polarimetric Synthetic Aperture Radar Compressive Sensing (DCPCS) simulation results. Compressive Sensing is a mathematical technique which can capture and represent compressible signals at sampling rates significantly below the Nyquist rate. DCPCS is a technique which enhances Compressive Sensing techniques using known physical antenna crosstalk values. The DCPCS technique enables reconstruction of fully polarimetric signals whilst only measuring part of the signal, reducing data capture requirements
Gamma Protection Factor for a Surrogate Armored Vehicle Exposed to the US Army Fast Burst Reactor
Get PDFThis work measures the Gamma Protection Factor (GPF) of a steel cube, which is meant to serve as a surrogate for armored vehicles. The GPF is measured at the White Sands Missile Range Fast Burst Reactor (FBR) and is modeled using MCNP® v6.2 transport simulation software. When exposed to the FBR, the GPF is found to depend roughly linearly on the distance between the reactor core and steel cube. The GPF is determined to be 1.176 ± 0.00067 at 9.21 m, 1.098 ± 0.0011 at 26.16 m, and 1.033 ± 0.00082 at 42.92 m. MCNP® estimates the GPF for the same scenario as 1.124 ± 0.011 at 9.21 m and 1.282 ± 0.018 at 26.16 m. This work utilizes a new configuration of the FBR with the irradiation target located on an external access ramp, and serves as a proof of concept for future experimental measurements
Comparing the Return of Investment of Maintenance and Repair Treatments on Airfield Pavements
Get PDFTwo decades of taking risks with infrastructure has led to a $33B backlog in deferred maintenance and recapitalization for the USAF, with expectations that this amount will triple in the next three decades. As this reality materializes, it becomes evident that the condition of infrastructure under the care of the USAF will undergo accelerated degradation. To address and rectify this situation, the Infrastructure Investment Strategy (I2S) was introduced. While the policy commits to bolstering the infrastructure budget to two percent of replacement value, it also acknowledges the necessity of implementing complementary strategies to effectively course correct. One strategy implied in the policy involves leveraging data to make cost-effective decisions. This research aligns with this strategy by analyzing airfield inspection data from four distinct USAF installations to determine the return on investment of various airfield pavement investments. Three analyses, leveraging multiple regression analysis, were conducted to compare various treatments: one focusing on benefits only, followed by short-term cost effectiveness and long-term cost-effectiveness. Outcomes from the analyses are intended to help engineers make well-informed airfield pavement decisions, ultimately supporting the goal of the I2S
Machine Learning Predictions of Electricity Transfers Between Balancing Authorities in the Carolinas
Get PDFClimate change through reduced streamflow, increased temperatures, and other factors impacts the efficiency of energy generation systems. The United States electric grid is comprised of a large network of balancing authorities engaged in trading electricity to maintain balance between supply and demand. The generation of electricity, a pivotal component of this balance, is impacted by climate change and weather variability as well as the growing demand for energy. Several hydro climatological factors such as streamflow, air temperature, and wind speed significantly influence the efficiency of power plant electricity generation. Due to the exchange of electricity between balancing authorities, impacts to electricity generation in one region could have negative effects on other regions, creating additional vulnerabilities in the electric grid. This study analyzes how hourly electricity trade of balancing authorities in the Carolinas (CAR) region can be predicted using hourly wind speed, air temperature, and streamflow data. The study uses random forest machine learning models to determine electricity transfer patterns based on the balancing authority’s electricity generation and exports. The results imply that streamflow is a significant predictor in electricity exchange of this region, highlighting drought as a notable vulnerability in the regional electric grid. However, there are limited predictive capabilities for seasonal variables such as time-of-day and day-of-week. This research adds to the existing body of knowledge within the energy-water nexus to highlight the coupling of these resources in the electricity trade