Design Sensitivity Research Articles

The integration of En route flow optimization, complex network clustering, and rule-based approach to airspace sub-sectorization for enhanced air traffic monitoring

This study proposes the use of a novel integrated framework for 2D en route airspace sub-sectorization. The integrated framework combines the multi-commodity flow optimization approach, complex network clustering approach, and Minimum Bounding Geometry (MBG)-coupled Rule-based Approach for boundary design. A decomposition-based discrete particle swarm optimization (DPSO) is used to solve the clustering problem. The output of the flow optimization is used as a guiding standard for the DPSO. Experimentations were performed using the Indian airspace sector to validate the framework and DPSO was run for different maximum number of generations (maxgen). The findings reveal that the multi-commodity flow approach captures system-wide flow operations. Clustering results corresponding to maxgen=100 and maxgen=150 perform best in terms of equitable and balanced distribution of cluster size and traffic load. The MBG-coupled Rule-based Approach leads to compact and convex sub-sector boundary design. Major implications of this research include dynamic adaptability of the integrated framework, increased sensitivity of sector design to network evolution, and a computationally tractable framework. The higher controllability of the proposed framework also offers an increased acceptance among practitioners.

Impact of Higher Harmonics of Gravitational Radiation on the Population Inference of Binary Black Holes

Templates modeling just the dominant mode of gravitational radiation are generally sufficient for the unbiased parameter inference of near-equal-mass compact binary mergers. However, neglecting the subdominant modes can bias the inference if the binary is significantly asymmetric, very massive, or has misaligned spins. In this work, we explore if neglecting these subdominant modes in the parameter estimation of nonspinning binary black hole mergers can bias the inference of their population-level properties such as mass and merger redshift distributions. Assuming the design sensitivity of the advanced LIGO-Virgo detector network, we find that neglecting subdominant modes will not cause a significant bias in the population inference, although including them will provide more precise estimates. This is primarily because asymmetric binaries are expected to be rarer in our detected sample, due to their intrinsic rareness and the observational selection effects. The increased precision in the measurement of the maximum black hole mass can help in better constraining the upper mass gap in the mass spectrum.

Leptogenesis in the minimal flipped SU(5) unification

We study the prospects of thermal leptogenesis in the framework of the minimal flipped SU(5) unified model in which the right-handed (RH) neutrino mass scale emerges as a two-loop effect. Despite its strong suppression with respect to the unification scale that tends to disfavor leptogenesis in the standard Davidson-Ibarra regime (and a notoriously large washout of the N1-generated asymmetry owing to a toplike Yukawa entry in the Dirac neutrino mass matrix) the desired ηB∼6×10−10 can still be attained in several parts of the parameter space exhibiting interesting baryon and lepton number violation phenomenology. Remarkably enough, in all these regions the mass of the lightest left-handed (LH) neutrino is so low that it yields mβ≲0.03 eV for the effective neutrino mass measured in beta decay, i.e., an order of magnitude below the design sensitivity limit of the KATRIN experiment. This makes the model potentially testable in the near future. Published by the American Physical Society 2024

Robust optimization of hypoid gear contact performance considering tooth form error: Design sensitivity and Pareto front

Optimization of hypoid gear contact performance is challenging due to its nonconvex nature and the handling of non-linear constraints involving complex gear contact behavior. In addition, the contact performance in the existing optimization schemes is highly reliant on the manufacturing quality, for example, the uncertain tooth form errors induced by machining tolerances and blade wear are usually ignored. To tackle these problems, a robust optimization methodology is proposed for hypoid gear contact performance. A finite element/contact mechanics model is established, which considers the stochastic tooth form errors following a Gaussian distribution model. The non-linear constraints are incorporated to avoid edge contact under loaded conditions, and tooth surface interference due to error. This methodology guarantees the feasible solution space and reduces the optimization complexity by the independent identification model. The identification model of the optimal solution is flexible in the parameter selection while keeping tooth depth. This non-deterministic problem is optimized based on the pattern search method. The Pareto front and design sensitivity analysis demonstrate the effectiveness and robustness of the proposed optimization methodology.

Constraining gravitational wave velocities using gravitational and electromagnetic wave observations of white dwarf binaries

ABSTRACT Although the general theory of relativity (GR) predicts that gravitational waves (GWs) have exactly the same propagation velocity as electromagnetic (EM) waves, many theories of gravity beyond GR expect otherwise. Accurate measurement of the difference in their propagation speed, or a tight constraint on it, could be crucial to validate or put limits on theories beyond GR. The proposed future space-borne GW detectors are poised to detect a substantial number of Galactic white dwarf binaries (GWDBs), which emit the GW as semimonochromatic signals. Concurrently, these GWDBs can also be identified as optical variable sources. Here we proposed that allocating a GWDB’s optical light curve and contemporaneous GW signal can be used to trace the difference between the velocity of GW and EM waves. Simulating GW and EM wave data from 14 verification binaries (VBs), our method constrains propagation-originated phase differences, limiting the discrepancy between the speed of light (c) and GW ($c_{GW}$). Through the utilization of LISA’s design sensitivity and the current precision in optical observation on GWDB, our study reveals that a four-year observation of the 14 recognized VBs results in a joint constraint that confines $\Delta c/c$ ($\Delta c = c_{\mathrm{GW}} - c$) to the range of $-2.1\times 10^{-12}$ and $4.8\times 10^{-12}$. Additionally, by incorporating this constraint on $c_{\mathrm{GW}}$, we are able to establish boundaries for the mass of the graviton, limiting it to $m_{\mathrm{g}}\le 3\times 10^{-23}\, e\mathrm{V}\,c^{-2}$, and for the parameter associated with local Lorentz violation, $\bar{s}_{00}$, constrained within the range of $-3.4\times 10^{-11}\le \bar{s}_{00}\le 1.5\times 10^{-11}$.

Simulation Study on Constraining Gravitational Wave Propagation Speed by Gravitational Wave and Gamma-ray Burst Joint Observation on Binary Neutron Star Mergers

Theories of modified gravity suggest that the propagation speed of gravitational waves (GW) v g may deviate from the speed of light c. A constraint can be placed on the difference between c and v g with a simple method that uses the arrival time delay between GW and electromagnetic wave simultaneously emitted from a burst event. We simulated the joint observation of GW and short gamma-ray burst signals from binary neutron star merger events in different observation campaigns, involving advanced LIGO (aLIGO) in design sensitivity and Einstein Telescope (ET) joint-detected with Fermi/GBM. As a result, the relative precision of constraint on v g can reach ∼10−17 (aLIGO) and ∼10−18 (ET), which are one and two orders of magnitude better than that from GW170817, respectively. We continue to obtain the bound of graviton mass m g ≤ 7.1(3.2) × 10−20 eV with aLIGO (ET). Applying the Standard-Model Extension test framework, the constraint on v g allows us to study the Lorentz violation in the nondispersive, nonbirefringent limit of the gravitational sector. We obtain the constraints of the dimensionless isotropic coefficients s¯00(4) at mass dimension d = 4, which are −1×10−15<s¯00(4)<9×10−17 for aLIGO and −4×10−16<s¯00(4)<8×10−18 for ET.

Topological design of soft substrate acoustic metamaterial for mechanical tuning of sound propagation

The design of tunable acoustic waves is crucial in phononic crystals (PnCs), as acoustic waves exhibit continuous variation across diverse frequency ranges in practical applications. While there have been research efforts on tunable PnCs, existing design strategies predominantly rely on predetermined topology and scatterer shapes based on empirical experience. This reliance poses challenges in ensuring customized and reversible tuning of the bandgap. In this work, we present a customized tunable PnC design model and solution strategy based on soft substrates, which enables reversible tuning of a specific frequency/order bandgap. The designed structure consists of a soft substrate and crystalline columns dispersed in the soft substrate and air. The relative positions of the scatterers in the air are changed by stretching the substrate, thereby realizing the modulation of sound propagation. Since soft materials have both material nonlinearities and complex geometrical variations that are difficult to obtain design sensitivity information, the material-field series expansion topology optimization approach is employed to achieve custom tunable design of the bandgap. The paper presents simulation-based analyses and experimental verification of the customized bandgap opening and closing. The results demonstrate a close alignment between theoretical predictions of propagation curves and experimental findings. This concurrence serves as evidence that the soft-substrate PnC, derived through topology optimization, effectively facilitates the adjustment of bandgaps of arbitrary orders and enables switching between various acoustic functions.

Sensitivity of optimal double-layer grid designs to geometrical imperfections and geometric nonlinearity conditions in the analysis phase

Sensitivity of optimal double-layer grid designs to geometrical imperfections and geometric nonlinearity conditions in the analysis phase

Process design and global sensitivity analysis of hydrogen fuel station with dual-operating modes for a sustainable H2 city: Iterative optimization-based simulation using generalized disjunctive programming

This study proposes a novel process involving dual-mode operation for an on-site hydrogen (H2) refueling station. In particular, two distinct H2 production technologies, steam methane reforming (SMR), and autothermal reforming (ATR), are simultaneously considered, which enables a flexible operational mode that responds to operational variability. By synergistically combining the technical advantages of these two technologies (i.e., the low cost of SMR and the short start-up and shut-down times of ATR), the proposed fuel station can reduce a H2 storage tank cost, which is needed to respond to demand fluctuations. To achieve our goal, we developed iterative optimization-based simulation (IOS) framework. The proposed framework determines the optimal design configuration (e.g., the storage facilities and the capacity of production) and the dual-mode operational strategy (e.g., on/off timing) under demand fluctuations and given CO2 emission targets. The case study showed that lower storage costs and offset the increased capital cost of the production facility, thereby leading to a low H2 supply cost of 3.60 USD/kg and a production capacity of 1.2 tons/day. We then performed a global sensitivity analysis to provide a comprehensive strategy and practices for the deployment of the proposed system over demand levels, regional demand fluctuation, and CO2 emission targets.

Accurate and efficient boundary method for isogeometric shape design sensitivity analysis considering tangential divergence of non-smooth boundary

Accurate and efficient boundary method for isogeometric shape design sensitivity analysis considering tangential divergence of non-smooth boundary

A reduced order/simplified method for uncertainty quantification on the floating wind turbine design basis

The cost of floating wind turbines (FWTs) is currently higher than onshore and bottom fixed offshore wind turbines. An important step towards more cost-efficient FWT structures is understanding the uncertainties and how they affect the design performance. On the path towards developing a fully probabilistic design approach, an important initial step is defining the variables and uncertainties that significantly impact the final design performance. This study aims to conduct a design sensitivity analysis on a FWT system consisting of the VolturnUS Semisubmersible floater coupled with an IEA 15 MW turbine. First, a Python-based design evaluation framework is implemented that computes operational limit states as a function of design input parameters defining the floater design. The system responses and the loads are obtained using Horizontal Axis Wind turbine simulation Code 2nd generation (HAWC2). Time domain outputs of the design evaluation framework are compared to a frequency domain response using Quick Load Analysis of Floating Wind Turbines (QuLAF). Initial results provide that buoyancy column diameter and the floater radius have the highest effects on the general floater response.

Enhanced electrochemical detection of chikungunya virus through aptasensor modification with origami paper-based ternary nanocomposite

Electrochemical sensors have drawn significant attention due to their crucial significance in the early detection of infectious illnesses, signifying their critical importance in diagnostic applications. This study’s proposed novel aptasensor exhibits a distinctive origami-based ePAD design, utilizing a unique silver-gold and zinc oxide (Ag-Au-ZnO) ternary nanocomposite for enhanced charge-transfer properties. Composite nanomaterials have a lower toxicity level, a higher signal enhancement capacity, increased sensitivity, improved conductivity, superior solubility, enhanced resolution capabilities, and a more straightforward functionalization process than individual nanomaterials. Employing paper, an economically advantageous substrate amenable to large-scale production with an origami-based ePAD is a critical enhancement of the sensor’s commendable attributes. Categorized as precision tools with an eco-conscious design, these sensors stand out for their streamlined manufacturing of environmentally sensitive substrates. This research capitalizes on the inherent foldability of paper to construct a three-dimensional multi-angular aptasensor, demonstrating cutting-edge specificity for chikungunya virus (CHIKV) detection. X- ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), UV–vis spectroscopy, and Fourier transmission infrared spectroscopy (FTIR) characterized the nanocomposites. This study also includes aptamers as outstanding and sensitive instruments for quick diagnostic applications. With the use of Cyclic Voltammetry (CV), the analytical response of the aptasensor was carefully evaluated. The study demonstrates a broad linear detection range spanning from 1 ng/ml to 10 µg/ml, with an impressively low limit of detection (LOD) at 1 ng/ml for the CHIKV antigen (CHIKV-Ag), underscoring the novelty and heightened sensitivity of this aptasensor design. Moreover, the aptasensor successfully detects CHIKV antigens in serum samples, and a long stability test demonstrates its practical utility and long-term stability for clinical applications. The proposed study concludes by introducing a novel origami-based paper-based analytical device (ePAD) as a promising tool for the quick, precise, and selective identification of the CHIKV antigen as well as its affordability, easy fabrication, and suitability of POCT testing makes an excellent diagnosing technique in resource-limited settings.

Innovations in architectural and environmental design: From methodologies to technology and cultural sensitivity

This comprehensive paper delves into the multifaceted world of contemporary architectural and environmental design, exploring an array of methodologies that emphasize sustainability, technological innovation, and socio-cultural integration. It begins by discussing the Integrated Design Process (IDP), which fosters early-stage collaboration across various disciplines, illustrated by the example of Seattles Bullitt Center. The paper then explores the principles of Biophilic Design, highlighting its positive impacts on human health and well-being, as seen in Singapores Khoo Teck Puat Hospital. The concept of Adaptive Reuse is explored next, emphasizing its role in sustainable urban development, with the Tate Modern in London serving as a case study. Further, the paper examines Green Building Technologies, Digital Design and Simulation Tools like BIM, and Smart Building Systems, showcasing their contributions to sustainable and efficient building management. The final sections discuss the importance of Community Engagement, Cultural Sensitivity in Design, and Inclusive Design, stressing the need for architecture that resonates with community values and is accessible to all. Through these discussions, the paper provides an insightful look into the current trends and future directions in architecture and environmental design, advocating for a holistic approach that balances functionality, sustainability, and cultural relevance.

The sensitivity of innovative techniques for measuring low levels of radon in the environment using passive detectors

In recent years, there has been a significant surge in interest in measuring low radon levels in the environment. These measurements are valuable, particularly for identifying radon priority areas as required by the European Council Directive 2013/59/EURATOM and for research related to climate change. Due to the limited sensitivity of existing radon detectors/monitors in addressing these challenges, substantial efforts have been devoted to developing new designs. This report compares the sensitivity of several innovative designs with that of existing passive radon monitors. These novel designs incorporate alpha track detectors, including large area low background detectors, with activated carbon fabric used as an efficient radon adsorber/radiator. Recent innovative solutions to mitigate the impact of temperature and humidity on detectors using adsorbers are also discussed. The background signal of detectors intended for use in these novel designs is examined, and their sensitivity is evaluated. The findings demonstrate that these novel designs have the potential to significantly enhance the sensitivity of long-term radon measurements, surpassing the detectors currently in widespread use by more than an order of magnitude.

On non-detection of gamma-ray bursts in three compact binary merger events detected by LIGO

ABSTRACT The joint detection of the gravitational wave (GW) event GW170817 and the short-duration gamma-ray burst (SGRB) event GRB 170817A, marked the beginning of GW multimessenger astronomy and confirmed that binary neutron star mergers are progenitors of at least some SGRBs. An estimated joint detection rate of 0.3–1.7 per year between the LIGO-Hanford, LIGO-Livingston, and Virgo GW network at design sensitivity, and the Fermi Gamma-ray Burst Monitor was predicted. However, to date, the GW170817/GRB 170817A joint detection has been the only event of its kind so far. Taking into account that SGRBs are narrowly beamed and are emitted perpendicular to the orbital plane of the binary system, we propose that previous mergers involving neutron stars, were orientated such that observation of the emitted SGRB along this narrow jet was not possible. To support this hypothesis we have estimated the inclination of the binary systems for previously detected Binary Neutron Star (BNS) and Black Hole Neutron Star (BHNS) mergers through GW analysis. This analysis was performed using bilby, a python based Bayesian inference library, to estimate the inclination of the BNS events GW170817 and GW190425, and the BHNS events GW190917_114630 and GW200115_042309. The results obtained in this study indicate that these binaries may have had inclinations greater than 33° with respect to the line of sight from Earth, an upper limit on the viewing angle set from observations of GRB 170817A. This then suggests that the observation of the emitted SGRB from these past mergers might not have been possible.

The effect of social anxiety on threat acquisition and extinction: a systematic review and meta-analysis.

Although exposure-based therapy has been found to be effective at alleviating symptoms of social anxiety disorder, it often does not lead to full remission, and relapse after treatment is common. Exposure therapy is based on theoretical principles of extinction of conditioned fear responses. However, there are inconsistencies in findings across experiments that have investigated the effect of social anxiety on threat conditioning and extinction processes. This systematic review and meta-analysis aimed to examine whether elevated levels of social anxiety are associated with abnormalities in threat conditioning and extinction processes. A second aim was to examine the sensitivity of various study designs and characteristics to detect social anxiety-related differences in threat conditioning and extinction. A systematic search was conducted, which identified twenty-three experiments for inclusion in the review. The findings did not demonstrate compelling evidence that high levels of social anxiety are associated with atypical threat conditioning or extinction. Further, when systematically examining the data, there was no convincing support that the use of a particular psychophysiological measure, subjective rating, or experimental parameter yields more consistent associations between social anxiety and conditioning processes during threat acquisition or extinction. Meta-analyses demonstrated that during threat extinction, the use of anxiety ratings as a dependent variable, socially relevant unconditioned stimuli, and a higher reinforcement schedule produced more detectable effects of social anxiety on compromised extinction processes compared to any other dependent variable (subjective or physiological) or experimental parameter. Overall, the results of this study suggest that social anxiety is not reliably related to deficits in conditioning and extinction processes in the context of laboratory-based Pavlovian conditioning paradigms.

Multi-material topology optimization with a direct meshless local Petrov–Galerkin method applied to a two-dimensional boundary value problem

ABSTRACT This work presents a novel approach for the solution of multi-material topology optimization problems of elastic structures coupling the Direct Meshless Local Petrov–Galerkin (DMLPG) method with the Gradual Bi-direction Evolutionary Structural Optimization (gBESO) method. In recent years, meshless methods have been used in several engineering fields, showing some advantages compared to mesh-based methods. DMLPG is a truly meshless method, which achieves results with good accuracy and computational efficiency, avoiding the numerical integration of complicated shape functions by adopting low-degree polynomials. In the proposed algorithm, DMLPG is used to obtain smooth nodal displacements, strains and stresses, and gBESO updates the structural geometry based on design sensitivity values of the compliance while it gradually increases the Young's modulus of the material. The optimization problem minimizes the compliance objective function subject to volume constraints. Numerical examples demonstrate the applicability and validity of the technique.

Directional Multi-Resonant Micro-Electromechanical System Acoustic Sensor for Low Frequency Detection.

This paper reports on the design, modeling, and characterization of a multi-resonant, directional, MEMS acoustic sensor. The design builds on previous resonant MEMS sensor designs to broaden the sensor's usable bandwidth while maintaining a high signal-to-noise ratio (SNR). These improvements make the sensor more attractive for detecting and tracking sound sources with acoustic signatures that are broader than discrete tones. In-air sensor characterization was conducted in an anechoic chamber. The sensor was characterized underwater in a semi-anechoic pool and in a standing wave tube. The sensor demonstrated a cosine-like directionality, a maximum acoustic sensitivity of 47.6 V/Pa, and a maximum SNR of 88.6 dB, for 1 Pa sound pressure, over the bandwidth of the sensor circuitry (100 Hz-3 kHz). The presented design represents a significant improvement in sensor performance compared to similar resonant MEMS sensor designs. Increasing the sensitivity of a single-resonator design is typically associated with a decrease in bandwidth. This multi-resonant design overcomes that limitation.

Machine learning models based on ultrasound and physical examination for airway assessment

PurposeTo demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters. MethodsThis is a prospective non-consecutive cohort of patients undergoing elective surgery. We collected as predictor variables age, sex, BMI, OSA, Mallampatti, thyromental distance, bite test, cervical circumference, cervical ultrasound measurements, and Cormack-Lehanne class after laryngoscopy. We univariate analyzed the relationship of the predictor variables with the Cormack-Lehanne class to design machine learning models by applying the random forest technique with each predictor variable separately and in combination. We found each design's AUC-ROC, sensitivity, specificity, and positive and negative predictive values. ResultsWe recruited 400 patients. Cormack-Lehanne patients≥III had higher age, BMI, cervical circumference, Mallampati class membership≥III, and bite test≥II and their ultrasound measurements were significantly higher. Machine learning models based on physical examination obtained better AUC-ROC values than ultrasound measurements but without reaching statistical significance. The combination of physical variables that we call the “Classic Model” achieved the highest AUC-ROC value among all the models [0.75 (0.67−0.83)], this difference being statistically significant compared to the rest of the ultrasound models. ConclusionsThe use of machine learning models for diagnosing VAD is a real possibility, although it is still in a very preliminary stage of development. Clinical registryClinicalTrials.gov: NCT04816435.

DarkGEO: a large-scale laser-interferometric axion detector

Axions and axion-like particles (ALPs) are leading candidates for dark matter. They are well motivated in many extensions of the standard model and supported by astronomical observations. We propose an iterative transformation of the existing facilities of the gravitational-wave detector and technology testbed GEO600, located near Ruthe in Germany, into a kilometre-scale upgrade of the laser-interferometric axion detector LIDA. The final DarkGEO detector could search for coincident signatures of axions and ALPs and significantly surpass the current constraints of both direct searches and astrophysical observations in the measurement band from 10−16 to 10−8eV. We discuss design parameters and sensitivities for the configurations of the different iteration steps as well as technical challenges known from the first LIDA results. The proposed DarkGEO detector will be well suited to probe the mass-coupling parameter space associated with predictions from theoretical models, like grand-unified theories, as well as from astrophysical evidence, like the cosmic infrared background.