Quantum Fourier transform to estimate drive cycles

Drive cycles in vehicle systems are important determinants for energy consumption, emissions, and safety. Estimating the frequency of the drive cycle quickly is important for control applications related to fuel efficiency, emission reduction and improving safety. Quantum computing has established the computational efficiency that can be gained. A drive cycle frequency estimation algorithm based on the quantum Fourier transform is exponentially faster than the classical Fourier transform. The algorithm is applied on real world data set. We evaluate the method using a quantum computing simulator, demonstrating remarkable consistency with the results from the classical Fourier transform. Current quantum computers are noisy, a simple method is proposed to mitigate the impact of the noise. The method is evaluated on a 15 qubit IBM-q quantum computer. The proposed method for a noisy quantum computer is still faster than the classical Fourier transform.

Experimental investigation of the transonic buffet cycle on a supercritical airfoil

Transonic buffet behaviour of the supercritical airfoil OAT15A was investigated experimentally at flow conditions $$Ma=0.7$$ M a = 0.7 and $$\alpha =3.5^\circ $$ α = 3 . 5 ∘ , using schlieren and particle image velocimetry (PIV). The general behaviour of the buffet cycle was characterised with short-exposure schlieren visualisation and phase-averaged PIV measurements. A spectral analysis showed that the shock oscillation occurs with a dominant contribution at 160 Hz (St = 0.07, in good agreement with the literature) and between 25 and 55 % of the chord of the airfoil. Proper Orthogonal Decomposition (POD) was applied to the PIV data to extract the main modes connected with buffet. It is found that the first three most energetic modes capture around 65 % of the total fluctuating kinetic energy. The first and the third modes have a main frequency peak at 160 Hz and are well representing the separated area and the shock oscillation. The second mode was, instead, associated with an asymmetrical behaviour of the separated area and of the shear layer and displays a main peak at 320 Hz, being double the main buffet cycle frequency. Finally, it was shown that by using the 11 most energetic POD modes, an accurate reduced-order model (ROM) is obtained, which when subtracted from the instantaneous velocity fields allows the visualisation of the small-scale structures present in the flow, such as the upstream travelling waves (UTWs) and the vortex shedding in the separated area near the trailing edge. The analysis allowed to estimate the velocity of the UTWs, obtaining values in good agreement with the literature. In contrast, the analysis of the vortex dynamics in the trailing edge area revealed that vortices shed at the shock foot, which convect downstream in an area detached from the airfoil surface, cannot be considered responsible for the creation of UTWs in view of the mismatch in frequency of the two phenomena. Graphic abstract

Quantum Fourier Transform to Estimate Drive Cycles

Drive cycles in vehicle systems are important determinants for energy consumption, emissions, and safety. Estimating the frequency of the drive cycle quickly is important for control applications related to fuel efficiency, emission reduction and improving safety. Quantum computing has established the computational efficiency that can be gained. A drive cycle frequency estimation algorithm based on the quantum Fourier transform is exponentially faster than the classical Fourier transform. The algorithm is applied on real world data set. We evaluate the method using a quantum computing simulator, demonstrating remarkable consistency with the results from the classical Fourier Transform. Current quantum computers are noisy, a simple method is proposed to mitigate the impact of the noise. The method is evaluated on a 15 qbit IBM-q quantum computer. The proposed method for a noisy quantum computer is still faster than the classical Fourier transform.

Torsional Fatigue Test Applicable to Helical Spring Material Used in Candu Fuel Channel Spacers

In a particular nuclear application, separation between structural components is maintained by a helical spring such that the separating load bears across the diameter of the spring coils. Relative motion between the structural components due to changing load and temperature is accommodated by rolling of the spring. This rolling motion while under radial load results in cyclic loading of the spring material. Fatigue analysis of the cyclic loading must take into consideration the material degradation due to the unique operating environment, so testing of ex-service material is required. Standard fatigue test specimens are not possible due to the small dimensions of the spring component. Cyclic stress may be applied to the material via a reciprocating rolling motion as per the operating conditions but this approach has practical limitations with respect to cycle frequency and uncertainty in stress response. A fatigue test system has been developed in which cyclic stress is achieved by applying torsional load with respect to the axis of the helical spring. This load translates into a pure bending state of stress in the cross-section of the coils. The relationship between applied load and stress is achieved analytically through curved beam analysis. Some practical considerations in the test setup are discussed along with supporting analysis, and results obtained with specimens taken from pre-service components are presented. The outcome of the tests is compared to applicable data and it is concluded that the test method is effective in producing valid fatigue data.

HAGP: A Heuristic Algorithm Based on Greedy Policy for Task Offloading with Reliability of MDs in MEC of the Industrial Internet

In the Industrial Internet, computing- and power-limited mobile devices (MDs) in the production process can hardly support the computation-intensive or time-sensitive applications. As a new computing paradigm, mobile edge computing (MEC) can almost meet the requirements of latency and calculation by handling tasks approximately close to MDs. However, the limited battery capacity of MDs causes unreliable task offloading in MEC, which will increase the system overhead and reduce the economic efficiency of manufacturing in actual production. To make the offloading scheme adaptive to that uncertain mobile environment, this paper considers the reliability of MDs, which is defined as residual energy after completing a computation task. In more detail, we first investigate the task offloading in MEC and also consider reliability as an important criterion. To optimize the system overhead caused by task offloading, we then construct the mathematical models for two different computing modes, namely, local computing and remote computing, and formulate task offloading as a mixed integer non-linear programming (MINLP) problem. To effectively solve the optimization problem, we further propose a heuristic algorithm based on greedy policy (HAGP). The algorithm achieves the optimal CPU cycle frequency for local computing and the optimal transmission power for remote computing by alternating optimization (AP) methods. It then makes the optimal offloading decision for each MD with a minimal system overhead in both of these two modes by the greedy policy under the limited wireless channels constraint. Finally, multiple experiments are simulated to verify the advantages of HAGP, and the results strongly confirm that the considered task offloading reliability of MDs can reduce the system overhead and further save energy consumption to prolong the life of the battery and support more computation tasks.

High-resolution mapping of the period landscape reveals polymorphism in cell cycle frequency tuning

Many biological oscillators exhibit widely tunable frequency in adapting to environmental changes. Although theoretical studies have proposed positive feedback as a mechanism underlying an oscillator's large tunability, there have been no experiments to test it. Here, applying droplet microfluidics, we created a population of synthetic cells, each containing a cell-cycle oscillator and varying concentrations of cyclin B mRNAs for speed-tuning and positive-feedback inhibitors for modulating network interactions, allowing a continuous mapping of the cell-cycle period landscape in response to network perturbation. We found that although the cell cycle's high tunability to cyclin B can reduce with Wee1 inhibition, the reduction is not as great as theoretically predicted, and another positive-feedback regulator, PP2A, may provide additional machinery to ensure the robustness of cell cycle period tunability. Remarkably, we discovered polymorphic responses of cell cycles to the PP2A inhibition. Droplet cells display a monomodal distribution of oscillations peaking at either low or high PP2A activity or a bimodal distribution with both low and high PP2A peaks. We explain such polymorphism by a model of two interlinked bistable switches of Cdk1 and PP2A where cell cycles exhibit two different oscillatory modes in the absence or presence of PP2A bistability.

ESTIMATION OF THE EFFICIENCY OF FLEXIBLE PRODUCTION SYSTEMS AND ROBOTIC COMPLEXES USING SIMULATION

The article presents a methodology for forecasting and analyzing the effectiveness of the use of flexible production systems and robotic systems. Simulation modeling and queuing theory are used as analysis tools. The production program for the release of products, which has a certain nomenclature and production volumes, is represented by a flow of applications. The production process is modeled over time and various technological situations are predicted. The computational experiment is conducted on the basis of the developed program using the object-oriented programming paradigm in Python. A probabilistic model of the dependence of the quality indicators of the line on the production program for manufacturing parts is implemented. Variants of production programs are presented in the form of combinations of dispersion fields of stages of the life cycle: frequency of receipt of parts and pro-cessing time on machine tools. The frequency of receipt of workpieces on the processing line is ap-proximated by an exponential law; the time of mechanical processing on machines is approximated by the law of normal distribution. A number of series of computational experiments have been carried out and their results have been analyzed, which characterize the stability of the line operation through the values of quality indicators: changeable loading of machine tools, loading of a parts accumulator, the probability of its overflow. The main regularities are revealed that provide high indicators of the shift loading of equipment, as well as the factors leading to their decrease.

Classification of Cross-Country Ski Skating Sub-Technique Can Be Automated Using Carrier-Phase Differential GNSS Measurements of the Head’s Position

Position–time tracking of athletes during a race can provide useful information about tactics and performance. However, carrier-phase differential global navigation satellite system (dGNSS)-based tracking, which is accurate to about 5 cm, might also allow for the extraction of variables reflecting an athlete’s technique. Such variables include cycle length, cycle frequency, and choice of sub-technique. The aim of this study was to develop a dGNSS-based method for automated determination of sub-technique and cycle characteristics in cross-country ski skating. Sub-technique classification was achieved using a combination of hard decision rules and a neural network classifier (NNC) on position measurements from a head-mounted dGNSS antenna. The NNC was trained to classify the three main sub-techniques (G2–G4) using optical marker motion data of the head trajectory of six subjects during treadmill skiing. Hard decision rules, based on the head’s sideways and vertical movement, were used to identify phases of turning, tucked position and G5 (skating without poles). Cycle length and duration were derived from the components of the head velocity vector. The classifier’s performance was evaluated on two subjects during an in-field roller skiing test race by comparison with manual classification from video recordings. Classification accuracy was 92–97% for G2–G4, 32% for G5, 75% for turning, and 88% for tucked position. Cycle duration and cycle length had a root mean square (RMS) deviation of 2–3%, which was reduced to <1% when cycle duration and length were averaged over five cycles. In conclusion, accurate dGNSS measurements of the head’s trajectory during cross-country skiing contain sufficient information to classify the three main skating sub-techniques and characterize cycle length and duration.

On the mechanism of three-body adhesive wear in turning

The paper reveals a hypothesis regarding the adhesive mechanism in metal cutting and its mechanical dynamics. One steel grade, 34CrNiMo 6, 285 HB, and one set of coatings on the cutting tool are reviewed. The adhesive mechanism is a transient vibration, including a feedback system limited by the plastic deformation in the chip. The vibration shows as a cluster of waves with stochastic duration in time. It starts up again after a stochastic lapse of silence. The cycle frequency is around 12.5 kHz and the internal excitation is twice that frequency, as the cutting speed and feed are 200 m/min and 0.2 mm, respectively. The adhesive frequency and amplitude are influenced by the cutting speed and the current wear status. The adhesion is monitored by the sound waves emanating from vibrations in the chip, the part still in the workpiece.

Coupling between fast and slow oscillator circuits in Cancer borealis is temperature-compensated

Coupled oscillatory circuits are ubiquitous in nervous systems. Given that most biological processes are temperature-sensitive, it is remarkable that the neuronal circuits of poikilothermic animals can maintain coupling across a wide range of temperatures. Within the stomatogastric ganglion (STG) of the crab, Cancer borealis, the fast pyloric rhythm (~1 Hz) and the slow gastric mill rhythm (~0.1 Hz) are precisely coordinated at ~11°C such that there is an integer number of pyloric cycles per gastric mill cycle (integer coupling). Upon increasing temperature from 7°C to 23°C, both oscillators showed similar temperature-dependent increases in cycle frequency, and integer coupling between the circuits was conserved. Thus, although both rhythms show temperature-dependent changes in rhythm frequency, the processes that couple these circuits maintain their coordination over a wide range of temperatures. Such robustness to temperature changes could be part of a toolbox of processes that enables neural circuits to maintain function despite global perturbations.