Large Machines Research Articles

Transcription-translation coupling: Recent advances and future perspectives.

The flow of genetic information from the chromosome to protein in all living organisms consists of two steps: (1) copying information coded in DNA into an mRNA intermediate via transcription by RNA polymerase, followed by (2) translation of this mRNA into a polypeptide by the ribosome. Unlike eukaryotes, where transcription and translation are separated by a nuclear envelope, in bacterial cells, these two processes occur within the same compartment. This means that a pioneering ribosome starts translation on nascent mRNA that is still being actively transcribed by RNA polymerase. This tethering via mRNA is referred to as 'coupling' of transcription and translation (CTT). CTT raises many questions regarding physical interactions and potential mutual regulation between these large (ribosome is ~2.5 MDa and RNA polymerase is 0.5 MDa) and powerful molecular machines. Accordingly, we will discuss some recently discovered structural and functional aspects of CTT.

3DFlex: determining structure and motion of flexible proteins from cryo-EM

Modeling flexible macromolecules is one of the foremost challenges in single-particle cryogenic-electron microscopy (cryo-EM), with the potential to illuminate fundamental questions in structural biology. We introduce Three-Dimensional Flexible Refinement (3DFlex), a motion-based neural network model for continuous molecular heterogeneity for cryo-EM data. 3DFlex exploits knowledge that conformational variability of a protein is often the result of physical processes that transport density over space and tend to preserve local geometry. From two-dimensional image data, 3DFlex enables the determination of high-resolution 3D density, and provides an explicit model of a flexible protein’s motion over its conformational landscape. Experimentally, for large molecular machines (tri-snRNP spliceosome complex, translocating ribosome) and small flexible proteins (TRPV1 ion channel, αVβ8 integrin, SARS-CoV-2 spike), 3DFlex learns nonrigid molecular motions while resolving details of moving secondary structure elements. 3DFlex can improve 3D density resolution beyond the limits of existing methods because particle images contribute coherent signal over the conformational landscape.

Design of O-ring with skeleton seal of cutter changing robot storage tank gate for large diameter shield machine

Faced with high pressure and high humidity environment, the seal of the storage cabin gate is the key to ensure the reliable frequent cutter replacing operation for shield machine. In this paper, the design criteria of the gate side seals was proposed. And the numerical analysis model of O-ring seal with skeleton was established. The influence of key structural parameters on the sealing performance was studied. The combination optimization parameters of the seal were obtained. The rationality of the seal structure is verified through the gate sealing performance test. It provides reference for the design and optimization of the sealing structure used in deep-sea tunnel shield.

Design, computational and experimental investigation of a small-scale turbopump for organic Rankine cycle systems

The hydraulic design, computational analysis, and experimental investigations of a high-speed small-scale turbopump for mobile waste heat recovery applications based on organic Rankine cycle systems are presented in this paper. Such applications demand high-pressure rise, lightweight, and compact pumping systems with simple construction. The investigated turbopump features an unshrouded 37.75 mm tip diameter single-stage centrifugal pump equipped with eight radial blades, eight splitters blades, and a rectangular axisymmetric volute. The pump should deliver 0.28 kg/s of mass flow rate with a pressure rise of 20 bar at a designed rotational speed of 25,000 rpm. Due to uncertainties observed in employing state-of-the-art 1-d methods that are valid for much larger machines, computational fluid dynamics is utilized to obtain a design meeting the specifications. The pump’s performance is evaluated experimentally at different rotational speeds, mass flow rates, and impeller tip clearances. The excellent agreement between experimental data and predictions from computational fluid dynamics validates the design methodology and computational results. The turbopump’s characteristics are then utilized to estimate the possible performance improvement of a target organic Rankine cycle using the novel turbopump instead of a commercial multi-stage centrifugal pump. The comparison suggests that the novel turbopump increases the efficiency of the target organic Rankine cycle by 0.3 % points and decreases its back-work ratio by nearly 50 %. The novel turbopump is approximately ten times more compact compared to commercial systems.

Optimal Efficiency Control of Wind Mill Induction Generator Using Loss Minimization Technique

Improvement of the operating efficiency of generators used in large wind power generation systems becomes important since such a large machine's power loss is not negligible. In the conventional method integral controller is used to reduce the power loss by up to 25 % at low wind speeds. The proposed PID controller method is based on flux level reduction, where the flux level is computed from the machine model for the optimum d-axis current of the generator. For the vector-controlled induction generator, the d-axis current controls the excitation level to minimize generator loss. In contrast, the q-axis current controls the generator torque, by which the speed of the induction generator is controlled according to the variation of the wind speed in order to produce the maximum output power, thereby improve the efficiency of the induction generator.

The role of complexity for digital twins of cities.

We argue that theories and methods drawn from complexity science are urgently needed to guide the development and use of digital twins for cities. The theoretical framework from complexity science takes into account both the short-term and the long-term dynamics of cities and their interactions. This is the foundation for a new approach that treats cities not as large machines or logistic systems but as mutually interwoven self-organizing phenomena, which evolve, to an extent, like living systems.

Phone Charger Using Sun Tracking Solar Panel

Abstract: This design uses solar energy from the light, also stores it and eventually converts it into electric energy. Electric energy is used to power a wide variety of devices, from small appliances like toasters and blenders to large industrial machines. It is also used to charge batteries, power lights, and provide heat and cooling. Electric energy is also used to generate electricity for homes and businesses. In our design solar panels absorb the energy and temperature detectors descry the temperature and change the direction of the solar panel to follow the direction of the light. therefore, temperature detector plays an important part in our design. The electricity stored in the capacitor is released into the electronics through the circuit. The capacitor acts as a buffer, allowing the current to flow at a steady rate. This helps to protect the electronics from sudden surges in current that could damage them. In the preface, the main way of the design are handed, also, the purpose and significance of design are shown. In the discussion section, the details of rendering, solid work delineation and factual work are examined. The experimental setup lists the accoutrements that are used in the design and show how the process is carried out to achieve the pretensions.

Data-driven multiscale simulation of solid-state batteries via machine learning

The battery cell performance is determined by electro-chemo-mechanical mechanisms on different length scales. Though there exist multi-field multiscale simulation frameworks, the high computation cost prevents their wide application. It is even more challenging when it comes to all-solid-state batteries where the influence of the interface damage and delamination between the solid electrolyte and cathode active material plays a critical role in cell performance and degradation. In this contribution, we propose a novel multiscale strategy based on large datasets and machine learning. Thereby a large dataset of simulations is obtained at the microscale for electrolyte-active material two-phase representative elements by employing a coupled chemo-mechanical model with varying materials and state variables. The data is then used to train a surrogate model based on a neural network. The surrogate model is capable of predicting the microscopic behavior with respect to the theories and thermodynamics law but much more efficient to access soon after it is trained sufficiently well. The surrogate model is then employed in the multi-field two-level framework to predict the cell performance, particularly the impact of interface damage on the capacity loss. By comparing it with the original multi-field two-level simulation results, the data-driven multiscale strategy is shown to be promising with high accuracy and efficiency, demonstrating the large potential of data-driven multiscale simulations for lithium-ion battery design.

NOISE MAPPING IN THE TURBINE AREA AT PT POMI

Background: One of the problems faced by industrial companies that use large machines and work equipment is noise. Steam power plant companies will certainly face noise problems in their work areas. PT. Paiton Operation and Maintenance Indonesia is one of the private power generation companies in East Java which manages three units of PLTU (Steam-Electric Power Plant) which in the process operates using a turbo generator. In addition, this company uses machines and equipment that produce noise that can potentially interfere with the health of the workers. Purpose: To map the noise with Golden Surfer software and to analyze the control efforts that had been carried out. Method: This research used an observational method and the analysis was done using Golden Surfer software. Result: The results of this study indicated that in general the noise that occurred in the turbine area exceeded the threshold value which was >85 dB. Furthermore, the results of the mapping showed the distribution pattern of noise levels that occurred in the turbine area starting from the first floor to the fifth floor. Noise control efforts were also carried out by the company, including noise measurements, scheduled preventive maintenance for machine repairs, safety sign, audiometric checks, work procedures, and PPE. Conclusion: In addition to this noise mapping, noise control efforts that have been carried out by the company will reduce the risk of health problems for workers. Thus, noise mapping can be used as a basic reference for companies to be able to determine additional noise control as an effort to prevent and control noise.

Data related to: "Inelastic N2+H2 collisions and quantum-classical rate coefficients: Large Datasets and Machine Learning predictions"

Data related to: "Inelastic N2+H2 collisions and quantum-classical rate coefficients: Large Datasets and Machine Learning predictions"

From memristive devices to neuromorphic systems

Progress in hardware and algorithms for artificial intelligence (AI) has ushered in large machine learning models and various applications impacting our everyday lives. However, today's AI, mainly artificial neural networks, still cannot compete with human brains because of two major issues: the high energy consumption of the hardware running AI models and the lack of ability to generalize knowledge and self-adapt to changes. Neuromorphic systems built upon emerging devices, for instance, memristors, provide a promising path to address these issues. Although innovative memristor devices and circuit designs have been proposed for neuromorphic computing and applied to different proof-of-concept applications, there is still a long way to go to build large-scale low-power memristor-based neuromorphic systems that can bridge the gap between AI and biological brains. This Perspective summarizes the progress and challenges from memristor devices to neuromorphic systems and proposes possible directions for neuromorphic system implementation based on memristive devices.

Variable-Coefficient Dynamic Modeling Method for a Ball Screw Feed System in the No-Extra-Load Running State

In a ball screw feed system of high-speed/high-acceleration machine tools, large frictional and inertial forces may change the real contact state of the kinematic joints, resulting in changes in the contact and transmission stiffnesses and, hence, changes in the dynamic characteristics of the system. In this study, a variable–coefficient dynamic modeling method for a ball screw feed system is proposed, considering the influence of changes in the no-extra-load running states, such as position, speed, and acceleration. Based on Timoshenko beam elements with two nodes and four DOFs, an equivalent dynamic model of a ball screw feed system is established using the hybrid element method. The expression for the equivalent axial stiffness of individual kinematic joints is derived, considering the influence of the feed speed/acceleration under the no-extra-load running state of the system. In addition, the stiffness and mass of the screw shafts on both sides of the screw nut are calculated, considering the influence of the system’s feed position. Hence, we obtain the total stiffness and mass of the system in the no-extra-load running state and analyze the natural frequency. Finally, we conduct validation experiments on a ball screw feed system of a large gantry-type machine tool with different no-extra-load running states.

Temporal logic explanations for dynamic decision systems using anchors and Monte Carlo Tree Search

For many automated perception and decision tasks, state-of-the-art performance may be obtained by algorithms that are too complex for their behavior to be completely understandable or predictable by human users, e.g., because they employ large machine learning models. To integrate these algorithms into safety-critical decision and control systems, it is particularly important to develop methods that can promote trust into their decisions and help explore their failure modes. In this article, we combine the anchors methodology with Monte Carlo Tree Search to provide local model-agnostic explanations for the behaviors of a given black-box model making decisions by processing time-varying input signals. Our approach searches for descriptive explanations for these decisions in the form of properties of the input signals, expressed in Signal Temporal Logic, which are highly likely to reproduce the observed behavior. To illustrate the methodology, we apply it in simulations to the analysis of a hybrid (continuous-discrete) control system and a collision avoidance system for unmanned aircraft (ACAS Xu) implemented by a neural network.

Design and Evaluation of Capacitive Smart Transducer for a Forestry Crane Gripper

Stable grasps are essential for robots handling objects. This is especially true for "robotized" large industrial machines as heavy and bulky objects that are unintentionally dropped by the machine can lead to substantial damages and pose a significant safety risk. Consequently, adding a proximity and tactile sensing to such large industrial machinery can help to mitigate this problem. In this paper, we present a sensing system for proximity/tactile sensing in gripper claws of a forestry crane. In order to avoid difficulties with respect to the installation of cables (in particular in retrofitting of existing machinery), the sensors are truly wireless and can be powered using energy harvesting, leading to autarkic, i.e., self-contained, sensors. The sensing elements are connected to a measurement system which transmits the measurement data to the crane automation computer via Bluetooth low energy (BLE) compliant to IEEE 1451.0 (TEDs) specification for eased logical system integration. We demonstrate that the sensor system can be fully integrated in the grasper and that it can withstand the challenging environmental conditions. We present experimental evaluation of detection in various grasping scenarios such as grasping at an angle, corner grasping, improper closure of the gripper and proper grasp for logs of three different sizes. Results indicate the ability to detect and differentiate between good and poor grasping configurations.

Article: The WTO Panel Report in United States - Safeguard on Washers (Part I)

This first part of the commentary on the panel decision in United States - Safeguard on Large Residential Washing Machines provides a summary and views on three issues addressed by the panel: the treatment of unforeseen developments (and the effect of obligations incurred under the GATT), the definition of the domestic industry, and the assessment of increased imports. The panel addressed these issues by relying extensively on the standard of review envisaged for the assessment of safeguard-related claims: the review of the existence of reasoned and adequate explanations. The panel also favoured consistency between the categories defined for the different instances of investigation. unforeseen developments, domestic industry, increased imports, reasoned and adequate explanation, safeguard on washers

The future belongs to dc: Edison will beat Tesla after all

For about a hundred years following the war of the currents (between Edison and Tesla), settled at the end of the 19th century in favor of ac, transmission and distribution (T&D) systems have followed the well-established architecture still in use today. The bulk of the power is generated using large synchronous machines (driven by steam and water turbines) that are connected to step-up transformers operating at 50 or 60 Hz. Then, extra high-voltage and ultrahigh-voltage ac transmission lines carry electric power over long distances to the consumption centers. Next, a series of cascaded step-down transformers reduce the voltage for the different functions (such as subtransmission and distribution) and applications (such as industrial, commercial, and residential). Since the 1950s, various high-voltage dc (HVdc) projects around the world have demonstrated that dc transmission is economically viable for high-power long-distance transmission.

Global domain fluid-thermal coupling modeling method and characteristics analysis for large capacity motor

—The global domain fluid-thermal characteristics study is challenging to perform due to the complicated ventilation arrangement and enormous volume for the large capacity electric machine. This paper uses the world's largest capacity non-superconducting low-speed induction motor, 6.5 MW, as the research object and proposes a global domain fluid-thermal characteristics calculation method. Firstly, the global domain fluid field model of the inner air path is established and solved. Then, the motor is divided into five subdomains according to the ventilation structure. The flow and pressure obtained from fluid field solutions are used as coupling parameters to couple each subdomain model, and an iterative solution is carried out based on the boundary condition continuity of the adjacent subdomains. The temperature distribution of each subdomain is obtained when the temperature difference is less than 0.1%. Finally, an experimental platform is built to verify the results. The maximum relative error between calculated and measured values is 1.67% for temperature and 4.92% for fluid velocity, which verifies the developed model's rationality and the proposed method's validity.

The Design of a Large-Scale Induction Heating Power Source for Organic Waste Digesters to Produce Fertilizer

Heating induction is a new environmentally friendly, energy-saving technology that offers a more effective performance than other common heaters. The energy-use efficiency of an inductor circuit is greater than 80 percent, while a biomass tank and tungsten coil have 70 percent and 51.8 percent efficiency, respectively. This method also produces more heat than any other forms of heating using gas or coal. The induction heating method has attracted significant interest and has seen application worldwide. Based on this important source of heating, we have designed and developed a large induction-heating machine with high energy to heat up a tank directly. The aim is to degrade organic waste as much as possible and convert it into an effective fertilizer by adding mesophilic microorganisms; the fertilizer transforming process takes no more than 24 h. The tank featured in our design has a 100-cm radius and is 155 in length; this is very large. The aim of this process is to reduce the amount of organic waste and thereby provide environmental benefits. To this end, we have designed a large, high-energy induction-heating machine (approximately 9.6 kilowatt) and used two machines in order to appropriately heat the tank for a large amount of organic-waste degradation. This research can be effectively applied to many heating methods in industry.

Ensuring the Authenticity of the Conservation and Reuse of Modern Industrial Heritage Architecture: A Case Study of the Large Machine Factory, China

The Large Machine Factory (LMF) was built in the complex historical context of the late Qing Dynasty (1840–1912). Its space and construction faithfully record the architectural and cultural fusion between Chinese and western traditions and mark the beginning of modern architectural techniques in China. Through historical data and empirical studies, the historical background and architectural characteristics of the LMF were analyzed, and interventions aimed at ensuring authenticity were established. The cultural significance and results of construction were considered two crucial elements in terms of outstanding characteristics. Comprehensive inspection and assessment strategies were discussed, with minimal intervention and interpretation principles. Preventive reinforcement of the foundation, complementary reinforcement of the main structures, restoration of the historic façade and environment, and adaptive spatial interventions were found to be effective ways to ensure authenticity. The principles of minimal intervention and interpretability, which include prevention, recognizability, invisibility, subsidiarity, and intertextuality, were proposed through a comparison with the literature and practical experience. This study provides an appropriate technical reference for ensuring authenticity in the conservation and reuse of modern historic buildings with complex contexts. We propose a new understanding of intervention principles and suggest a guiding intervention path that avoids the complexities arising from the generalized interpretations of authenticity.

Natiolectal Variation in Dutch Morphosyntax: A Large-Scale, Data-Driven Perspective

AbstractIn this article, we report a large-scale corpus study aimed at tackling the (controversial) question to what extent the European national varieties of Dutch, that is, Belgian and Netherlandic Dutch, exhibit morpho-syntactic differences. Instead of relying on a manual selection of cases of morphosyntactic variation, we first marshal large bilingual parallel corpora and machine translation software to identify semiautomatically, in an extensively data-driven fashion, loci of variation from various “corners” of Dutch grammar. We then gauge the distribution of con-structional alternatives in a nationally as well as stylistically stratified corpus for a representative selection of twenty alternation patterns. We find that natiolectal variation in the grammar of Dutch is far more prevalent than often assumed, especially in less edited text types, and that it shows up in inflection phenomena, lexically conditioned syntactic variation, and pure word order permutations. Another key finding is that many cases of synchronic probabilistic asymmetries reflect a diachronic difference between the two varieties: Netherlandic Dutch often tends to be ahead in cases of ongoing grammatical change, with Belgian Dutch holding on somewhat longer to obsolescent features of the grammar.*