Robust multi-fidelity design of a micro re-entry unmanned space vehicle

This article addresses the preliminary robust design of a small-scale re-entry unmanned space vehicle by means of a hybrid optimization technique. The approach, developed in this article, closely couples an evolutionary multi-objective algorithm with a direct transcription method for optimal control problems. The evolutionary part handles the shape parameters of the vehicle and the uncertain objective functions, while the direct transcription method generates an optimal control profile for the re-entry trajectory. Uncertainties on the aerodynamic forces and characteristics of the thermal protection material are incorporated into the vehicle model, and a Monte-Carlo sampling procedure is used to compute relevant statistical characteristics of the maximum heat flux and internal temperature. Then, the hybrid algorithm searches for geometries that minimize the mean value of the maximum heat flux, the mean value of the maximum internal temperature, and the weighted sum of their variance: the evolutionary part handles the shape parameters of the vehicle and the uncertain functions, while the direct transcription method generates the optimal control profile for the re-entry trajectory of each individual of the population. During the optimization process, artificial neural networks are utilized to approximate the aerodynamic forces required by the optimal control solver. The artificial neural networks are trained and updated by means of a multi-fidelity approach: initially a low-fidelity analytical model, fitted on a waverider type of vehicle, is used to train the neural networks, and through the evolution a mix of analytical and computational fluid dynamic, high-fidelity computations are used to update it. The data obtained by the high-fidelity model progressively become the main source of updates for the neural networks till, near the end of the optimization process, the influence of the data obtained by the analytical model is practically nullified. On the basis of preliminary results, the adopted technique is able to predict achievable performance of the small spacecraft and the requirements in terms of thermal protection materials

City-level air quality improvement in the Beijing-Tianjin-Hebei region from 2016/17 to 2017/18 heating seasons: Attributions and process analysis

With the implementation of clean air strategies, PM_(2.5) pollution abatement has been observed in the “2 + 26” cities in the Beijing-Tianjin-Hebei (BTH) region (referred to as the BTH2+26) and their surrounding areas. To identify the drivers for PM_(2.5) concentration decreases in the BTH2+26 cites from the 2016/17 heating season (HS1617) to the 2017/18 heating season (HS1718), we investigated the contributions of meteorological conditions and emission-reduction measures by Community Multi-Scale Air Quality (CMAQ) model simulations. The source apportionments of five sector sources (i.e., agriculture, industry, power plants, traffic and residential), and regional sources (i.e., local, within-BTH: other cities within the BTH2+26 cities, outside-BTH, and boundary conditions (BCON)) to the PM_(2.5) decreases in the BTH2+26 cities were estimated with the Integrated Source Apportionment Method (ISAM). Mean PM_(2.5) concentrations in the BTH2+26 cities substantially decreased from 77.4 to 152.5 μg m⁻³ in HS1617 to 52.9–101.9 μg m⁻³ in HS1718, with the numbers of heavy haze (daily PM_(2.5) ≥150 μg m⁻³) days decreasing from 17-77 to 5–30 days. The model simulation results indicated that the PM_(2.5) concentration decreases in most of the BTH2+26 cities were attributed to emission reductions (0.4–55.0 μg m⁻³, 2.3–81.6% of total), but the favorable meteorological conditions also played important roles (1.9–25.4 μg m⁻³, 18.4–97.7%). Residential sources dominated the PM_(2.5) reductions, leading to decreases in average PM_(2.5) concentrations by more than 30 μg m⁻³ in severely polluted cities (i.e., Shijiazhuang, Baoding, Xingtai, and Beijing). Regional source analyses showed that both local and within-BTH sources were significant contributors to PM_(2.5) concentrations for most cities. Emission controls in local and within-BTH sources in HS1718 decreased the average PM_(2.5) concentrations by 0.1–47.2 μg m⁻³ and 0.3–22.1 μg m⁻³, respectively, relative to those in HS1617. Here we demonstrate that a combination of favorable meteorological conditions and anthropogenic emission reductions contributed to the improvement of air quality from HS1617 to HS1718 in the BTH2+26 cities

Mobile robot positioning: Sensors and techniques

Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In search of a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This article provides a review of relevant mobile robot positioning technologies. The article defines seven categories for positioning systems: (1) Odometry, (2) Inertial Navigation, (3) Magnetic Compasses, (4) Active Beacons, (5) Global Positioning Systems, (6) Landmark Navigation, and (7) Model Matching. The characteristics of each category are discussed and examples of existing technologies are given for each category. The field of mobile robot navigation is active and vibrant, with more great systems and ideas being developed continuously. For this reason the examples presented in this article serve only to represent their respective categories, but they do not represent a judgment by the authors. Many ingenious approaches can be found in the literature, although, for reasons of brevily, not all could be cited in this article. © 1997 John Wiley & Sons, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34938/1/2_ftp.pd

Significant wintertime PM_(2.5) mitigation in the Yangtze River Delta, China, from 2016 to 2019: observational constraints on anthropogenic emission controls

Ambient fine particulate matter (PM_(2.5)) mitigation relies strongly on anthropogenic emission control measures, the actual effectiveness of which is challenging to pinpoint owing to the complex synergies between anthropogenic emissions and meteorology. Here, observational constraints on model simulations allow us to derive not only reliable PM_(2.5) evolution but also accurate meteorological fields. On this basis, we isolate meteorological factors to achieve reliable estimates of surface PM_(2.5) responses to both long-term and emergency emission control measures from 2016 to 2019 over the Yangtze River Delta (YRD), China. The results show that long-term emission control strategies play a crucial role in curbing PM_(2.5) levels, especially in the megacities and other areas with abundant anthropogenic emissions. The G20 summit hosted in Hangzhou in 2016 provides a unique and ideal opportunity involving the most stringent, even unsustainable, emergency emission control measures. These emergency measures lead to the largest decrease (∼ 35 µg m⁻³, ∼ 59 %) in PM_(2.5) concentrations in Hangzhou. The hotspots also emerge in megacities, especially in Shanghai (32 µg m⁻³, 51 %), Nanjing (27 µg m⁻³, 55 %), and Hefei (24 µg m⁻³, 44 %) because of the emergency measures. Compared to the long-term policies from 2016 to 2019, the emergency emission control measures implemented during the G20 Summit achieve more significant decreases in PM_(2.5) concentrations (17 µg m⁻³ and 41 %) over most of the whole domain, especially in Hangzhou (24 µg m⁻³, 48 %) and Shanghai (21 µg m⁻³, 45 %). By extrapolation, we derive insight into the magnitude and spatial distribution of PM_(2.5) mitigation potential across the YRD, revealing significantly additional room for curbing PM_(2.5) levels

High reduction of ozone and particulate matter during the 2016 G-20 summit in Hangzhou by forced emission controls of industry and traffic

Many regions in China experience air pollution episodes because of the rapid urbanization and industrialization over the past decades. Here we analyzed the effect of emission controls implemented during the G-20 2016 Hangzhou summit on air quality. Emission controls included a forced closure of highly polluting industries, and limiting traffic and construction emissions in the cities and surroundings. Particles with aerodynamic diameter lower than 2.5 μm (PM_(2.5)) and ozone (O_3) were measured. We also simulated air quality using a forecast system consisting of the two-way coupled Weather Research and Forecast and Community Multi-scale Air Quality (WRF-CMAQ) model. Results show PM_(2.5) and ozone levels in Hangzhou during the G-20 Summit were considerably lower than previous to the G-20 Summit. The predicted concentrations of ozone were reduced by 25.4%, whereas the predicted concentrations of PM_(2.5) were reduced by 56%

Biocompatibility and biofilm inhibition of N,N-hexyl,methyl-polyethylenimine bonded to Boston Keratoprosthesis materials

The biocompatibility and antibacterial properties of N,N-hexyl,methyl-polyethylenimine (HMPEI) covalently attached to the Boston Keratoprosthesis (B-KPro) materials was evaluated. By means of confocal and electron microscopies, we observed that HMPEI-derivatized materials exert an inhibitory effect on biofilm formation by Staphylococcus aureus clinical isolates, as compared to the parent poly(methyl methacrylate) (PMMA) and titanium. There was no additional corneal epithelial cell cytotoxicity of HMPEI-coated PMMA compared to that of control PMMA in tissue cultures in vitro. Likewise, no toxicity or adverse reactivity was detected with HMPEI-derivatized PMMA or titanium compared to those of the control materials after intrastromal or anterior chamber implantation in rabbits in vivo.Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies (Contract DAAD-19-D-0002