Gas turbines must now comply with much stricter emission control regulations. In fact, to combat the greenhouse effect, regulatory authorities have drastically reduced allowable emission levels. For example, in less than 12 years, the United States’ Clean Air Act issued the New Source Performance Standards (NSPS), which tightened the NOx emission margin of natural gas combustion (from 75 ppm to 10 ppm). On the other hand, despite those efforts, the high demand for energy produced by fossil-fueled gas turbines in power plants has resulted in dramatic increases in anthropogenic CO₂ and NO_x emitted by gas combustors. Most systems responsible for these undesirable emissions are directly linked to power generation, with gas turbines playing a pivotal role. Yet, gas turbines are still widely used in power plants and will continue to meet the growing demand. Therefore, sequestration and separation techniques such as Carbon Capture and Storage (CCS) and Air Separation Units (ASU) are essential to reduce CO₂ and NO_x emissions while allowing large amounts of power to be generated from these systems. This paper provides an in-depth examination of the current state of the art in alternative working fluids utilized in the power generation industry (i.e., gas turbines, combustion). In addition, this paper highlights the recent contribution of integrating separation techniques, such as air separation, steam methane reforming, and water-gas shifting, to the power generation industry to facilitate a continuous and adequate supply of alternative working fluids.

This research paper investigates the applicability and scalability of the Rotor Control Equivalent Turbulence Input models for multi-rotor vehicles. Initially, a Rotor Control Equivalent Turbulence Input model is developed for an isolated rotor using rotor RPM as the input and the rotor hub-load coefficient as the output. Subsequently, the model is applied to multi-rotor vehicle example to show that the effect of turbulence on vehicle response can be replicated using the Rotor Control Equivalent Turbulence Input models. This study further incorporates rotor collective deflections, which could be used in multi-rotor vehicles, to develop a collective input model. Additionally, the effect of altering rotor parameters on the Rotor Control Equivalent Turbulence Input model is studied and presented. The results demonstrate that the Rotor Control Equivalent Turbulence Input model effectively captures the turbulence-induced behaviors in multi-rotor vehicles, offering a generalizable and scalable framework for use to replicate the effect of turbulence in multi-rotor vehicles.

Understanding compressible flows over bluff bodies, such as circular cylinders, is critical for applications in aerospace engineering, space exploration, and astrophysics. However, the complexity of viscous and unsteady flows, compounded by compressibility effects, remains a challenge for experimental and computational methods. This study explores the compressible flow field of an impulsively started circular cylinder using Refined Potential Flow Theory (RPT), an analytical model that extends classical potential flow theory to include compressibility effects. The governing equations, boundary conditions, and refined stream function are developed to capture the density, velocity, and pressure fields in subsonic and transonic regimes. The results demonstrate that compressibility marginally increases vortex enstrophy at low Reynolds numbers, while its influence on wake flow stability diminishes at higher values. The study reveals that compressibility suppresses shear layer instability, reduces wake velocity deficits, and introduces smaller-scale structures that disrupt the inertial range of turbulence in the low subsonic regime. At higher Mach numbers (M∞≥0.6), local supersonic pockets and shock waves emerge, forming complex λ-shock systems and bow shocks. The predictions of the Strouhal number from RPT show marginal changes for 0.2≤M∞≤0.5, consistent with experimental and computational trends. Although RPT aligns with existing methods to capture key flow features, discrepancies in wake stability and recirculation zone dimensions highlight areas for further refinement. This research underscores the potential of RPT in developing optimization tools that complement experimental and numerical studies, offering valuable insights into compressible flow physics for engineering applications in high-altitude flight and space exploration.

Lightweight unmanned aerial vehicle (UAV) panels require electromagnetic interference (EMI) shielding with limited added mass and manageable manufacturing demands. This study compares seven experimentally reported thermoset carbon-fiber-reinforced polymer (CFRP) shielding configurations on a common X-band basis. The decision matrix combines paired mean shielding gain relative to each study’s matched pristine laminate, dry functional-modifier areal mass, and manufacturing and integration burden. TOPSIS and VIKOR were applied using reference weights of 0.40, 0.40, and 0.20. The polyaniline (PANI)-coated carbon-fabric CFRP containing 1 wt.% reduced graphene oxide/Fe₃O₄ hybrid (C4) ranked first by both methods, providing a 35.90 dB shielding gain at 13.26 g m⁻² dry modifier mass. PANI-decorated ACF-7/CFRP (C3) ranked second under TOPSIS, while the two-veil MXene/PEDOT:PSS/APP-modified reclaimed-carbon-fiber CFRP (C6) ranked second under VIKOR. C4 ranked first in 18 of the 19 TOPSIS weight-sensitivity cases and in all 19 VIKOR cases. Across the 243 bounded-input cases, both methods also kept C4 at first place. Under the stated UAV panel priorities, C4 is the preferred balanced configuration, while C3 is the low-mass alternative and C6 the shielding-prioritized alternative. The framework provides a traceable screening route while retaining source-specific mechanical evidence outside the weighted score.

This paper presents a novel step in the extension of subspace identification toward the direct identification of harmonic decomposition linear time-invariant models from nonlinear time-periodic system responses. The proposed methodology is demonstrated through examples involving the nonlinear time-periodic dynamics of a flapping-wing micro aerial vehicle. These examples focus on the identification of the vertical dynamics from various types of input–output data, including linear time-invariant, linear time-periodic, and nonlinear time-periodic input–output data. A harmonic analyzer is used to decompose the linear time-periodic and nonlinear time-periodic responses into harmonic components and introduce spurious dynamics into the identification, which make the identified model order selection challenging. A similar effect is introduced by measurement noise. The use of model order reduction and model-matching methods in the identification process is studied to recover the harmonic decomposition structure of the known system. The identified models are validated in the frequency and time domains.