Reliability-Based Analysis and Optimization of the Gravity Balancing Performance of Spring-Articulated Serial Robots with Uncertainties

This article proposes a method for analyzing the gravity balancing reliability of spring-articulated serial robots with uncertainties. Gravity balancing reliability is defined as the probability that the torque reduction ratio (the ratio of the balanced torque to the unbalanced torque) is less than a specified threshold. The reliability analysis is performed by exploiting a Monte Carlo simulation (MCS) with consideration of the uncertainties in the link dimensions, masses, and compliance parameters. The gravity balancing begins with a simulation-based analysis of the gravitational torques of a typical serial robot. Based on the simulation results, a gravity balancing design for the robot using mechanical springs is realized. A reliability-based design optimization (RBDO) method is also developed to seek a reliable and robust design for maximized balancing performance under a prescribed uncertainty level. The RBDO is formulated with consideration of a probabilistic reliability constraint and solved by using a particle swarm optimization (PSO) algorithm. A numerical example is provided to illustrate the gravity balancing performance and reliability of a robot with uncertainties. A sensitivity analysis of the balancing design is also performed. Lastly, the effectiveness of the RBDO method is demonstrated through a case study in which the balancing performance and reliability of a robot with uncertainties are improved with the proposed method.

On the uncertainty associated with detecting global and local mean sea level drifts on Sentinel-3A and Sentinel-3B altimetry missions

An instrumental drift in the Point Target Response (PTR) parameters has been detected on the Copernicus Sentinel-3A (S3A) altimetry mission. It could have an impact on sea level rise of a few tenths of mm yr−1. In order to accurately evaluate this drift, a method for detecting global and local mean sea level relative drifts between two altimetry missions is implemented. Associated uncertainties are also accurately calculated thanks to a detailed error budget analysis. A drift on both S3A and S3B GMSL is detected with values significantly higher than expected. For S3A, the relative GMSL drift detected is 1.0 mm yr−1 with Jason-3 and 1.3 mm yr−1 with SARAL/AltiKa. For S3B, the relative GMSL drift detected is −2.2 mm yr−1 with SARAL/AltiKa and −3.4 mm yr−1 with Jason-3. The drift detected at global level does not show detectable regional variations above the uncertainty level of the proposed method. The investigations led by the altimeter experts can now explain the origin of this drift for S3A, while it is still under investigation for S3B. The ability of the implemented method to detect a sea level drift with respect to the length of the common period is also analysed. We find that the maximum detectable sea-level drift over a 5 years period is 0.3 mm yr−1 at the global scale, and 1.5 mm yr−1 at local scales (2400 km). However, these levels of uncertainty do not meet the sea-level stability requirements for climate change studies.

Assessment and Evaluation in Active Learning Implementations: Introducing the Engineering Education Active Learning Maturity Model

With the technological changes experienced in the world in recent decades, society has changed as a whole, due to the speed and availability of information that exists today. As student attention decreases, critical thinking and Active Learning, which places the student at the center of the learning process, have gained prominence. Considering the growing popularity of these techniques, this article proposes the Engineering Education Active Learning Maturity Model (E2ALM2), a framework that allows practitioners to assess the current maturity of Active Learning implementation in a program or a course. E2ALM2 was built from a literature review of key success factors (KSF) for Active Learning implementations, which were divided into dimensions. Each KSF is composed of constructs, which are detailed with variables. Each variable has a proposed measurement method and an estimated uncertainty level. The framework can support diagnosis and practical improvements in real settings.

Sensitivity of Estimated Total Canopy SIF Emission to Remotely Sensed LAI and BRDF Products

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides new possibilities to estimate terrestrial gross primary production (GPP). To mitigate the angular and canopy structural effects on original SIF observed by sensors (SIFobs), it is recommended to derive total canopy SIF emission (SIFtotal) of leaves within a canopy using canopy interception (i0) and reflectance of vegetation (RV). However, the effects of the uncertainties in i0 and RV on the estimation of SIFtotal have not been well understood. Here, we evaluated such effects on the estimation of GPP using the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) model. The SCOPE simulations showed that the R2 between GPP and SIFtotal was clearly higher than that between GPP and SIFobs and the differences in R2 (ΔR2) tend to decrease with the increasing levels of uncertainties in i0 and RV. The resultant ΔR2 decreased to zero when the uncertainty level in i0 and RV was ~30% for red band SIF (RSIF, 683 nm) and ~20% for far-red band SIF (FRSIF, 740 nm). In addition, as compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIFobs at both red and far-red bands, SIFtotal derived using any combination of i0 (from MCD15, VNP15, and CGLS LAI products) and RV (from MCD34, MCD19, and VNP43 BRDF products) showed comparable improvements in estimating GPP. With this study, we suggest a way to advance our understanding in the estimation of a more physiological relevant SIF datasets (SIFtotal) using current satellite products.

A federated data-driven evolutionary algorithm for expensive multi-/many-objective optimization

Data-driven optimization has found many successful applications in the real world and received increased attention in the field of evolutionary optimization. Most existing algorithms assume that the data used for optimization are always available on a central server for construction of surrogates. This assumption, however, may fail to hold when the data must be collected in a distributed way and are subject to privacy restrictions. This paper aims to propose a federated data-driven evolutionary multi-/many-objective optimization algorithm. To this end, we leverage federated learning for surrogate construction so that multiple clients collaboratively train a radial-basis-function-network as the global surrogate. Then a new federated acquisition function is proposed for the central server to approximate the objective values using the global surrogate and estimate the uncertainty level of the approximated objective values based on the local models. The performance of the proposed algorithm is verified on a series of multi-/many-objective benchmark problems by comparing it with two state-of-the-art surrogate-assisted multi-objective evolutionary algorithms.

A method to measure the spectral responsivity of a photometer using optical excitations with arbitrary spectral distributions

The spectral responsivity of a photometer is usually measured using very narrow optical excitations, provided by a monochromator or a tuneable laser. This article describes a technique to measure the spectral responsivity using an arbitrary number of optical excitations having any type of spectral distribution. The problem is formulated as an inverse problem which is solved using a probabilistic approach based on Bayes’ theorem. The method requires a prior knowledge of the spectral responsivity, which can be proportional to the standard photopic function, with an uncertainty level related to the spectral match index of the photometer. Using this method, the estimation can be performed from data provided by a simple experimental set-up. The numerical application provides a stable and unique solution to the inverse problem, along with the estimation uncertainties. Using a tuneable LED source, the method was applied to an illuminance measurement head, giving an estimation of its spectral responsivity from 380 to 780 nm with a step of 1 nm. The results were in good agreement with data obtained by a monochromator-based technique. Our measurement had larger uncertainties towards the red and blue limits of the spectrum as the light source provided very little light at these wavelengths.

Optical Power Scale Realization by Laser Calorimeter after 45 Years of Operation

To calibrate laser power and energy meters, the National Institute of Standards and Technology (NIST) uses several detector-based realizations of the scale for optical radiant flux; these realizations are appropriate for specific laser power/energy ranges and optical coupling configurations. Calibrations from 1 μW to 2 W are currently based upon calorimeters. Validation by comparisons against other primary representations of the optical watt over the last two decades suggests the instruments operate well within their typical reported uncertainty level of 0.86 % with 95 % confidence. The dominant uncertainty contribution in the instrument is attributable to light scattered by the legacy window, which was not previously recognized. The inherent electro-optical inequivalence in the calorimeter’s response was reassessed by thermal modeling to be 0.03 %. The principal contributions to the overall inequivalence were corrected, yielding a shift in scale representation under 0.2 % for typical calibrations. With updates in several uncertainty contributions resulting from this reassessment, the resulting combined expanded uncertainty (k = 2) is 0.84 %, which is essentially unchanged from the previous result provided to calibration customers.

A new measurement of the 122Sb half-life

Following significant discrepancies observed when decay-correcting 122Sb γ-peak count rates to a reference time, we looked at the literature supporting the presently recommended 2.7238(2) d (1σ) 122Sb half-life value as the source of these discrepancies. Investigation revealed that the value was derived from an inconsistent dataset and was published without reporting details of the experiment nor the uncertainty budget. In this work we performed a new measurement of the 122Sb half-life by measuring the 122Sb decay of neutron-activated antimony samples using state-of-the-art γ-detection systems characterized in terms of efficiency drift and random pulse pile-up. The measurement was carried out in two different laboratories with the same method. The resulting 2.69454(39) d and 2.69388(30) d (1σ) 122Sb half-life values are in agreement at the evaluated 10–4 relative combined standard uncertainty level but are significantly lower (1.07% and 1.10% lower, respectively) than the preexisting recommended value.

Justification of the approach for reducing the geometric factor variability of the air objects coordinates determination system using MLAT technology.

Estimating results of the MLAT technology capabilities regarding accuracy of air basing radio sources positioning using ADS-B system signals depending on receiving points system geometric configuration are presented. Based on the obtained results, geometric configuration parameters of the MLAT system which most significantly affect the accuracy of estimating the airborne sources coordinates in the monitoring area are identified. The variant of the receiving points placement in control area which ensures a decrease in uncertainty level regarding coordinate estimation accuracy is proposed.

A powerful lidar system capable of 1 h measurements of water vapour in the troposphere and the lower stratosphere as well as the temperature in the upper stratosphere and mesosphere

A high-power Raman lidar system has been installed at the high-altitude research station Schneefernerhaus (Garmisch-Partenkirchen, Germany) at 2675 ma.s.l., at the side of an existing wide-range differential absorption lidar (DIAL). An industrial XeCl laser was modified for linearly polarized single-line operation at an average power of about 180 W. This high power and a 1.5 m diameter receiver allow us to extend the operating range for water-vapour sounding to 20 km for a measurement time of just 1 h, at an uncertainty level of the mixing ratio of 1 to 2 ppm. This was achieved for a vertical resolution varied between just 0.2 and 0.6 km in the stratosphere. The lidar was successfully validated with a balloon-borne cryogenic frost-point hygrometer (CFH). In addition, temperature measurements up to altitudes of around 87 km were demonstrated for 1 h of signal averaging. The system has been calibrated with the DIAL, the CFH and radiosondes.