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This paper's aim is to examine flow and heat transfer through vertical channels between parallel plates, which is of prime importance in the design of cooling systems for electronic equipment such as that of finned cold plates in general, plate‐and‐frame heat exchangers, etc.

Numerical and analytical solutions are presented to investigate the heat transfer enhancement and the pressure drop reduction due to buoyancy effects (for buoyancy‐aided flow) for the developing laminar mixed convection in vertical channel between parallel plates in the vicinity of the critical values of the buoyancy parameter (Gr/Re)crt that are obtained analytically. The numerical solutions are presented for a wide range of the buoyancy parameters Gr/Re that cover both of buoyancy‐opposed and buoyancy‐aided flow situations under each of the isothermal boundary conditions under investigation.

Buoyancy parameters greater than the critical values result in building‐up the pressure downstream of the entrance such that the vertical channel might act as a thermal diffuser with possible incipient flow reversal. Locations at which the pressure gradient vanishes and the locations at which the pressure‐buildup starts have been numerically obtained and presented for all the investigated cases.

The study is limited to the laminar flow situation.

The results clearly show that for buoyancy‐aided flow, the increase of the buoyancy parameter enhances the heat transfer and reduces the pressure drop across the vertical channel. These findings are very useful for cooling channel or chimney designs.

The study is original and presents new findings, since none of the previous studies reported the conditions for which pressure buildup might take place due to mixed convection in vertical channels between parallel plates.

A parabolic trough solar collector is an advanced concentrated solar power technology that significantly captures radiant energy. Solar power will help different sectors reach their energy needs in areas where traditional fuels are in use. This study aims to examine the sensitivity analysis for optimizing the heat transfer and entropy generation in the Jeffrey magnetohydrodynamic hybrid nanofluid flow under the influence of motile gyrotactic microorganisms with solar radiation in the parabolic trough solar collectors. The influences of viscous dissipation and Ohmic heating are also considered in this investigation.

Governing partial differential equations are derived via boundary layer assumptions and nondimensionalized with the help of suitable similarity transformations. The resulting higher-order coupled ordinary differential equations are numerically investigated using the Runga-Kutta fourth-order numerical approach with the shooting technique in the computational MATLAB tool.

The numerical outcomes of influential parameters are presented graphically for velocity, temperature, entropy generation, Bejan number, drag coefficient and Nusselt number. It is observed that escalating the values of melting heat parameter and the Prandl number enhances the Nusselt number, while reverse effect is observed with an enhancement in the magnetic field parameter and bioconvection Lewis number. Increasing the magnetic field and bioconvection diffusion parameter improves the entropy and Bejan number.

Nanotechnology has captured the interest of researchers due to its engrossing performance and wide range of applications in heat transfer and solar energy storage. There are numerous advantages of hybrid nanofluids over traditional heat transfer fluids. In addition, the upswing suspension of the motile gyrotactic microorganisms improves the hybrid nanofluid stability, enhancing the performance of the solar collector. The use of solar energy reduces the industry’s dependency on fossil fuels.

The variance between the winning bid and the owner's estimated cost (OEC) is one of the construction management risks in the pre-tendering phase. The study aims to enhance the quality of the owner's estimation for predicting precisely the contract cost at the pre-tendering phase and avoiding future issues that arise through the construction phase.

This paper integrated artificial neural networks (ANN), deep neural networks (DNN) and time series (TS) techniques to estimate the ratio of a low bid to the OEC (R) for different size contracts and three types of contracts (building, electric and mechanic) accurately based on 94 contracts from King Saud University. The ANN and DNN models were evaluated using mean absolute percentage error (MAPE), mean sum square error (MSSE) and root mean sums square error (RMSSE).

The main finding is that the ANN provides high accuracy with MAPE, MSSE and RMSSE a 2.94%, 0.0015 and 0.039, respectively. The DNN's precision was high, with an RMSSE of 0.15 on average.

The owner and consultant are expected to use the study's findings to create more accuracy of the owner's estimate and decrease the difference between the owner's estimate and the lowest submitted offer for better decision-making.

This study fills the knowledge gap by developing an ANN model to handle missing TS data and forecasting the difference between a low bid and an OEC at the pre-tendering phase.

This study aims to investigate the external effect of the economic growth target pressure of local governments on establishment-level SO₂ emissions.

Based on manually collected panel data of 74,058 China's industrial establishments and more than 330 thousand observations from CIED and ESR, the authors use a firm-fixed effect model, instrumental variables estimation and heterogeneity tests to identify the environmental externality of economic growth target pressure.

The establishments in cities that meet or slightly exceed the economic growth target experience greater negative externality measured by SO₂ emission intensity. This external effect is more pronounced in regions: with a strict and overweighted target setting; with stronger officials' promotion incentives; with a low degree of marketization; and in firms with great economic importance. The authors identify the underlying mechanisms of dependence on dirty industry and the relaxation of environmental enforcement. And the environmental protection constraints in 2007 mitigate the negative externality.

The paper sheds light on to what extent economic growth target pressure has a negative externality of pollution in China and how this pressure may conflict with environmental protection.

This paper complements prior research on the economic effects of economic growth targets, expands the knowledge on the determinants of establishment-level pollution emission from the perspective of target pressure and provides insight into the environmental externality that results from political factors.

Paint drying is a very important process in an industry where shorter drying time for productivity and lower energy consumption for production cost are required while maintaining the product’s painting quality. In the present study, a drying process in a line-type paint drying furnace equipped with nozzles for hot air supply and moving conveyer belt to dry painted automotive parts is numerically simulated for the flow and heat transfer inside the furnace to evaluate the quality of the drying or baking at the end of the drying process in a production line.

A baking window for a specific paint is used for judging the local degree of baking (DOB) of the painted parts, which can be useful to identify under-baked or over-baked locations of the painted parts, and hence the quality of the baking process.

Numerical results of a time history of temperatures at two monitoring points on the painted parts were obtained and compared to the measured data in an actual furnace and showed good agreement. Three types of paints were considered in the present study and numerical results showed different drying characteristics. In addition to the original furnace nozzle configuration, two more furnace nozzle configurations with different numbers, direction and speed of hot air supply were simulated to improve the furnace’s drying performance. As a result, a newly suggested nozzle configuration with quick drying paint can give us a remarkable improvement in surface averaged DOB compared to the original nozzle configuration with original paint.

The present simulation technique and DOB methodology can be used for the optimal design of a drying furnace.

THERE have been official links for the past twelve years between the Institute of Incorporated Work Study Technologists and Time and Motion Study. Many of its members have been valued contributors to our pages and the Institute has had editorial space for its news.

Aims to define the conceptual tools of Gregory Bateson's epistemology – the nature of difference, logical typing, and recursion – and to apply this to understanding how we can approach the analysis of ethnographic reports of the Bushman n/om‐kxaosi (shamans) and the Bushman rock art of Southern Africa.

The paper argues that kinesthetic interaction with n/om‐kxaosi provides a vehicle for learning their way of construing the world.

The n/om‐kxaosi have a kinesthetic lexicon and a set of dominant metaphors rooted to their ecstatic body expression that provide coherence to their ways of healing and spiritual understanding. The previously assumed incoherent nature of Bushman religious views noted by anthropologists is argued to have been the consequence of underestimating the importance Bushman thinking gives to circularity and transformation of all aspects of their experience.

Illuminates the analysis of the Bushman culture.

This paper aims to propose a novel integrated control method (ICM) for high-power-density non-inverting interleaved buck-boost DC-DC converter. To achieve high power conversion by conventional single phase DC-DC converter, inductor value must be increased. This converter is not suitable for industrial and high-power applications as large inductor value will increase the inductor current ripple. Thus, two-phase non-inverting interleaved buck-boost DC-DC converter is proposed.

The proposed ICM approach is based on the theory of integrated dynamic modeling of continuous conduction mode (CCM), discontinuous conduction mode and synchronizing parallel operation mode. In addition, it involves the output voltage controller with inner current loop (inductor current controller) to make a fair balancing between two stages. To ensure fast transient performance, proposed digital ICM is implemented based on a TMS320F28335 digital signal microprocessor.

The results verify the effectiveness of the proposed ICM algorithm to achieve high voltage regulating (under 0.01 per cent), very low inductor current ripple (for boost is 1.96 per cent, for buck is 1.1) and fair input current balance between two stages (unbalancing current less than 0.5A).

The proposed new ICM design procedure is developed satisfactorily to ensure fast transient response even under high load variation and the solving R right-half-plane HP zeros of the CCM. In addition, the proposed method can equally divide the input current of stages and stable different parallel operation modes with large input voltage variations.

The risks associated with digital innovation increasingly challenge value co-creation among stakeholders within the innovation ecosystem. Stakeholder collaboration is helpful in preventing risk occurrence. This study intends to explore the effects of different stakeholder collaboration strategies on risk prevention performance in a digital innovation ecosystem context.

A systematic literature analysis was first conducted to identify risk factors of digital innovation based on the technology–organization–environment (TOE) framework. Then, a bidimensional network model was constructed to visualize the collaborative relationships among stakeholders and the identified risks by focusing on a digital innovation case. The social network analysis method was applied to design stakeholder collaboration strategies from the ego and global network perspectives, and a simulation approach was conducted to evaluate the effects of the strategies on risk prevention performance.

The results validate the positive effect of stakeholder collaboration on risk prevention performance and reveal the important role of network reachability in formulating collaboration strategies. The strategy of strong–strong collaboration strategy can best enhance risk prevention performance like a “Matthew effect” in the digital innovation ecosystem.

First, risk identification based on the TOE framework provides a systematic list of risk factors for future digital innovation risk management research. Second, this study designs stakeholder collaboration strategies from a network perspective to enhance the understanding of the network status of each stakeholder and the network structure of the digital innovation ecosystem. Third, the simulation results reveal the effects of different collaboration strategies on risk prevention performance.