VTechWorks
VTechWorks provides global access to Virginia Tech scholarship, including journal articles, books, theses, dissertations, conference papers, slide presentations, technical reports, working papers, administrative documents, videos, images, and more by faculty, students, and staff. Faculty can deposit items to VTechWorks from Elements, including journal articles covered by the University open access policy. Email vtechworks@vt.edu for help.
Open Access Policy
Virginia Tech's open access policy enables researchers to deposit the accepted version of scholarly articles with no embargo.
Theses and Dissertations
Virginia Tech was first in the world to require ETDs in 1997, and continues to add scans of older theses and dissertations.
Open Textbooks
More than 50 freely available and openly licensed textbooks are among our most downloaded items.
Communities in VTechWorks
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Recent Submissions
Optimizing Spectrum Sharing: Models and Algorithms for Coexistence
Jai, Naru (Virginia Tech, 2026-11-09)
Advancing Long Duration Energy Storage: A Multiphysics Approach to Control, CFD and Grid Integration
Ashraf, Muhammad Mubashar (Virginia Tech, 2026-11-09)
Thermal energy is one of the most important resources in our daily lives with applications across nearly every sector including energy, processing industries, and electricity generation. As technology advances, using thermal energy effectively becomes increasingly important to avoid environmental impacts, reduce the high cost of handling, and limit energy waste across industrial sectors. Also the emerging technologies offer promising ways to tackle these challenges. Thermal energy storage (TES) is one such advancement. It stores excess heat and can act as an intermediary for the load balancing problems caused by the intermittency of renewable energy resources. Energy storage is generally categorized as short duration (< 10 h), long duration (> 10 h and < 200 h), and seasonal storage (> 200 h). This research broadly studies long duration energy storage (LDES) systems, since advances in these systems can play a critical role in enabling high-penetration renewable power systems and ensuring reliable grid operation over multi-hour to seasonal timescales. Particle-based LDES is one of several key technologies that can be integrated with existing thermal power systems and that offers a low cost of storage, among other benefits. This research contributes to the advancement of these systems by (1) implementing controls in pumped-thermal energy storage (PTES) and electro-thermal energy storage (ETES), which provides a road map for control systems; (2) developing and applying a computational fluid dynamics (CFD) model to investigate the thermal performance of a key component, a novel counterflow particle fluidized bed heat exchanger (PFB-HX), with validation against experimental results; and (3) investigating the grid integration opportunities of LDES systems. The first study develops a two-layered control strategy that dynamically adjusts the critical parameters in the system. The controls are first implemented in the PTES system and then, with the relevant information carried over, translated to the control of the ETES system. In this two-layered scheme, the first layer is the main controller that provides the control signals for all operations in the LDES system, while the second layer regulates the particle flow rate in the solar receiver for the hybrid PTES system and in the PFB-HX for the ETES system to achieve a consistent temperature and power output. The study clarifies the role and importance of consistent power output, along with its impact on system parameters such as round-trip efficiency, and identifies the control parameters that contribute to the commercial scale development of the ETES system. The second study investigates the thermal performance of the PFB-HX under counterflow conditions. Because the PFB-HX plays an important role in the overall efficiency and cost of the system, this study validates the computational model against experimental results and examines the sensitivity of the drag and heat transfer models and their effect on PFB-HX performance. The result is a road map for setting up the computational strategy used to study PFB-HXs, one that balances the accuracy of the results against computational time at full scale while offering key insights into the flow physics inside the fluidized bed during operation. The third study investigates the grid integration of LDES systems, highlighting the key challenges and devising a strategy for integration through the study of key performance parameters. Across all three thrusts, this research develops the methodologies and tools needed for continued work on LDES systems while contributing to the literature by answering several key questions. Collectively, this work advances control methodologies, deepens the understanding of particle-scale thermal dynamics, and clarifies the system-level benefits of LDES. The findings provide actionable guidance for the design and operation of next-generation PTES and ETES facilities, supporting the transition to a resilient, decarbonized power grid.
A Data-driven 3D Reconstruction Pipeline for Flying Bats
Hu, Yihao (Virginia Tech, 2026-11-09)
Bats are capable of highly dexterous flight maneuvers that rely heavily on highly articulated hand skeletons and malleable wing membranes. To understand the underlying mechanisms, large amounts of detailed data on bat flight kinematics are required. Conventional methods to obtain these data have been based on tracing landmarks and require substantial manual efforts. In this study, we present a markerless reconstruction pipeline that incorporates a physics simulator to estimate the full three-dimensional geometry of flying bats from synchronized high-speed video recordings. The pipeline employs an iterative optimization procedure that alternates between skeletal pose estimation and wing-membrane deformation optimization. The method was evaluated on 49 flight recordings comprising 73,451 targetpositive frame sets from five bat species recorded in a flight tunnel using 50 synchronized high-speed cameras. Successful reconstructions were obtained for 36,979 frame sets, yielding 66 continuous flight sequences spanning a variety of flight maneuvers and altitude behavior, including straight flight, gliding, turns, and S-curves. Reconstructions were evaluated using image-fitting accuracy, wing-surface curvature, reconstruction yield, and qualitative inspection.
Forest Disturbance Alters Water Yield but Not Catchment Drainage Behaviour
Evaristo, Jaivime; McGuire, Kevin J.; Jackson, C. Rhett (Wiley, 2026-10)
Forested headwater watersheds that share climate and broadly similar lithology are often assumed to behave hydrologically alike, and forest-disturbance studies typically emphasize changes in annual water yield. To test this assumption, we analysed daily streamflow records spanning approximately 40–88 years from 14 independent headwater watersheds at the Coweeta Hydrologic Laboratory. Recession constant k ranged from 11.2 to 38.7 days, and baseflow index BFI ranged from 0.558 to 0.820. WS27, WS36 and WS37, whose divides exceed approximately 1450 m elevation, formed a distinct short-k/low-BFI cluster, whereas we detected no difference between the seven reference and seven treated watersheds representing disturbed forests (Mann–Whitney U = 20, exact two-sided p = 0.62 for both k and BFI). The 1965–2022 WS7–WS2 record spans 58 water years, of which 56 met the paired completeness criterion. The 1977 WS7 clear-cut increased annual yield relative to the pre-cut calibration by about 260 mm in the first post-cut year and by 68 mm year−1 on average over 1977–1989; after 1990 yield was no longer elevated (slightly below the WS2 calibration, −29 mm year−1). In contrast, under the primary strict-decline recession definition, k showed no detectable reference-adjusted step change relative to WS2. The contrasts were +0.7 days (95% interval−1.1 to 2.5) post-cut and −0.8 days (−1.9 to 0.3) in the recovered era. In a sensitivity analysis, recession runs bridged 1- or 2-day plateaus at the archive's resolution of 0.01 cubic feet per second per square mile (CSM). The post-cut contrast was +8% to +11% of the pre-cut value (intervals excluding zero). Thus, a modest transient lengthening of k is not excluded. BFI rose by 0.014 (0.003–0.028) relative to WS2 during the post-cut era (0.012, 0.001–0.024, relative to WS18) and was no longer distinguishable from its pre-cut relation in the recovered era (−0.006, −0.013 to 0.002, relative to WS2). These results identify k and BFI as persistent drainage signatures at Coweeta. Although they do not directly measure storage volume or critical-zone thickness, these metrics can screen watersheds for contrasting recession and low-flow behaviour that persists through forest disturbance.
Tenko: A Streaming Intrusion Detection Framework with Context-Aware Anomaly Scoring
Banerjee, Soumya; Bhola, Sahil; Dave, Daksh; Shetty, Sachin; Burger, Eric W. (Institute of Electrical and Electronics Engineers, 2026-11)
Unsupervised intrusion detection systems (IDS) are appealing because they can identify previously unseen attacks without labeled data; however, many reconstruction-based detectors are sensitive to benign traffic variability in deployment. Packet-derived anomaly scores fluctuate, fixed thresholds become unstable, and instantaneous alerts generate persistent false positives in streaming and resource-constrained environments. In reconstruction-based detectors, this instability arises when observations lack multi-packet, partial-flow, or persistent entity-level context, while malicious activity is associated with entities evolving over time. We present Tenko, a lightweight unsupervised intrusion detection framework that augments packet-level detection with persistent context by synthesizing reconstruction-error observations into continuously updated node-level risk scores and conditioning each packet-level decision on the corresponding node’s behavioral state. An autoencoder-based detector provides instantaneous anomaly measurements, while temporal aggregation interprets these measurements using persistence and entity context, enabling operation under thresholds calibrated without labeled attack data. Across diverse attack scenarios, distribution shifts, and memory-constrained conditions, Tenko produces more consistent, lower-variance decision behavior while remaining computationally suitable for streaming gateway and IoT workloads under sequential trace replay. The results show that persistence-aware interpretation can improve the practical usability of reconstruction-based detection under benign-only training. At the same time, unavoidable false alarms for some traffic patterns and degradation under extreme distribution shift reflect the operational limits of unsupervised detection from a single benign reference regime. These findings indicate that, in deployment-constrained streaming environments, effective unsupervised intrusion detection depends less on instantaneous anomaly magnitude alone than on how anomaly evidence is accumulated and interpreted within a bounded operating regime.