Summary

Eng (ISSN 2673-4117) is an international, peer-reviewed open access journal which publishes original papers, critical reviews, rapid communications, technical notes, and discussions on all areas of engineering. Eng's aim is to encourage scientists to publish their experimental and theoretical research relating to engineering science and technology in as much detail as possible. There is no restriction on the maximum length of the papers. Launched in 2020, Eng was indexed in Scopus in 2023. The journal was subsequently included in the Emerging Sources Citation Index (ESCI, Web of Science) in March 2024 and Ei Compendex in April 2025. It holds a 2025 Impact Factor of 3.5 and is ranked JCR Q1 in the “ENGINEERING, MULTIDISCIPLINARY” category. Its 2025 CiteScore is 4.1, and it currently ranks Q2 in Scopus’ “Engineering (miscellaneous)” category.

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Topic Review
Human–Computer Interaction
Human–Computer Interaction (HCI) is an interdisciplinary academic and engineering field that investigates the reciprocal communicative relationships between human operators and computational systems across multiple layers of perception, cognition, action and feedback [1]. It examines how human users acquire information from system outputs, formulate cognitive intentions, execute control commands through input devices, and interpret system responses to accomplish intended task goals [2]. Its conceptual scope spans physical hardware interfaces, graphical software interfaces, haptic and auditory interaction channels, as well as the cognitive and ergonomic principles that govern effective and usable interaction design. HCI is not limited to any single device category or application domain; instead, it establishes fundamental principles governing human-machine communication that apply across desktop computing, mobile devices, industrial control systems and immersive environments, integrating perspectives from computer science, cognitive psychology, ergonomics, industrial design and information science [3].
  • 3
  • 21 Sep 2026
Topic Review
Supply Chain Management
Supply chain management refers to the integrated planning, coordination, execution, and control of all business activities associated with the flow of goods, services, information, and financial resources from raw-material sourcing through production, distribution, and final-product delivery to end customers across participating organisations within a supply-chain network [1]. It encompasses cross-organisational coordination among suppliers, manufacturers, logistics providers, distributors, and end-users, aiming to align material and information flows under defined operational, cost, and service-level objectives [2]. Unlike isolated intra-enterprise functional management, SCM emphasises end-to-end governance of the entire network boundary rather than optimisation of any single firm's internal departments in isolation. It covers both forward physical-product flow and reverse-logistics product returns, and it integrates demand forecasting, inventory planning, transportation scheduling, procurement decision-making, warehouse management, and customer-service fulfilment as interconnected components. The discipline treats the supply chain as an interdependent system in which local decisions by one member propagate effects throughout the network, and it seeks to balance total system cost against required service levels rather than minimising any single node's cost independently [3].
  • 4
  • 20 Sep 2026
Topic Review
Rock Mass Classification
Rock mass classification (or rock mass rating) is a quantitative empirical procedure by which the quality, competence, and expected engineering behavior of a jointed rock mass are summarized into a finite set of classes or an index number based on a small number of geomechanical parameters [1]. Typical input parameters include the uniaxial compressive strength of the intact rock, rock quality designation (RQD), joint spacing, joint condition (roughness, weathering, infilling), groundwater condition, and joint orientation relative to the excavation [2]. The two most widely used systems are the Rock Mass Rating (RMR) system of Bieniawski, which sums weighted ratings to classify the mass into five classes and to derive support recommendations, and the Q-system of Barton, Lien, and Lunde, which expresses rock-mass quality as a product of ratios of RQD, joint-set number, joint roughness, joint alteration, joint water reduction, and stress reduction factors [2][3]. Classification systems are distinguished from continuous rock-mass strength criteria (such as the Hoek–Brown failure criterion) by their empirical, table-based, and design-rule-oriented character.
  • 4
  • 18 Sep 2026
Topic Review
Solar Photovoltaic System
A solar photovoltaic (PV) system is an electrical system that converts incident solar radiation directly into electrical energy through the photovoltaic effect, in which photons absorbed by a semiconductor generate electron–hole pairs that are separated by a junction to produce direct-current electricity [1]. The fundamental conversion unit is the solar cell, a large-area semiconductor diode—most commonly based on crystalline silicon—whose p–n junction produces a photocurrent when illuminated and whose current–voltage characteristic defines its short-circuit current, open-circuit voltage, and maximum power point [2]. A complete PV system combines PV modules (interconnected arrays of cells) with balance-of-system components—including mounting structures, wiring, maximum-power-point-tracking electronics, and inverters that convert the generated direct current to alternating current for grid connection or off-grid storage [1]. The system is distinguished from solar thermal systems, which convert sunlight into heat rather than electricity, and from other power-generation sources by the direct solid-state conversion of photon energy to electrical energy without moving thermodynamic cycles [2]. The electrical output of a module is characterized under standardized reference irradiance and temperature conditions so that different systems can be compared on a common basis [3].
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  • 18 Sep 2026
Topic Review
Bootstrap Confidence Intervals
Bootstrap confidence intervals are interval estimates of a population parameter constructed by resampling the observed data with replacement, rather than by relying on an analytic sampling distribution or an assumed parametric form [1]. In the bootstrap procedure, a large number of bootstrap replicates are drawn from the original sample, each replicate having the same size as the sample and containing observations drawn uniformly at random with replacement [2]. The statistic of interest is recomputed on each replicate, yielding the bootstrap distribution of the statistic; this distribution serves as an empirical estimate of the sampling distribution from which standard errors, bias estimates, and confidence intervals are derived [1]. Several interval constructions exist: the percentile interval uses the empirical quantiles of the bootstrap distribution; the basic bootstrap interval reflects the difference between the estimate and its bootstrap quantiles; and bias-corrected and accelerated intervals adjust for bias and skewness in the bootstrap distribution [3]. Bootstrap confidence intervals are distinguished from analytic intervals by their reliance on computationally intensive resampling and by their weaker assumptions about the underlying distribution [2].
  • 5
  • 18 Sep 2026
Topic Review
Single-Slope Analog-to-Digital Converter
A single-slope analog-to-digital converter (single-slope ADC) is an integrating-type ADC that converts an input analog voltage into a digital word by measuring the time required for a linear ramp waveform to cross the input voltage [1]. The conversion begins with the reset of an integrator capacitor; the integrator then generates a voltage that ramps linearly at a known constant rate while a counter is incremented by a fixed-frequency clock [2]. When the ramp voltage equals the input voltage, a comparator stops the counter, and the counter reading is proportional to the input voltage, yielding the digital output [1]. Because the conversion relies on a single ramp and a single comparison per conversion, the architecture is simple, and its differential linearity is largely determined by the linearity of the ramp generator and the stability of the clock [2]. The single-slope ADC is distinguished from the dual-slope (dual-ramp) ADC, which uses an additional de-integration interval to cancel errors due to ramp slope and component drift [2]. Its conversion time is signal-dependent and relatively long, which places it among low-speed, high-resolution ADC architectures [3].
  • 4
  • 18 Sep 2026
Topic Review
Reynolds-Averaged Navier-Stokes
The Reynolds-averaged Navier–Stokes (RANS) equations are the time-averaged form of the Navier–Stokes equations obtained by decomposing each instantaneous flow variable into a mean (time-averaged) component and a fluctuating turbulent component, then averaging the equations over time or ensemble [1]. Substituting the decomposed velocity and pressure into the instantaneous Navier–Stokes equations and averaging introduces an additional unknown term—the Reynolds stress tensor, representing the momentum transport by turbulent fluctuations—so that the RANS system is no longer closed and requires a turbulence model to relate the Reynolds stresses to the mean flow field [1]. The closure problem is resolved by eddy-viscosity models, which express the Reynolds stresses through an eddy (turbulent) viscosity obtained from algebraic, one-equation, or two-equation transport models, or by Reynolds-stress transport models that solve transport equations for the individual stress components [2]. RANS equations predict only the statistically averaged mean flow rather than resolved turbulent motions, and are distinguished from direct numerical simulation, which resolves all scales, and from large-eddy simulation, which resolves large eddies while modeling only small scales [3].
  • 2
  • 18 Sep 2026
Topic Review
One-Dimensional Solar Cell
A one-dimensional solar cell is a computational or physical model in which the photovoltaic device structure and its governing equations are treated as varying only along a single spatial coordinate—usually the depth normal to the illuminated surface—while material properties are assumed uniform in the lateral directions [1]. The model solves, along that coordinate, Poisson’s equation for the electrostatic potential coupled to the electron and hole continuity equations and the drift–diffusion current equations, together with optical generation as a function of depth and wavelength [2]. Carrier transport, recombination (radiative, Shockley–Read–Hall, Auger), and the resulting current–voltage and quantum-efficiency characteristics are computed under boundary conditions at the front and back contacts [3]. The one-dimensional approximation reduces a multilayer thin-film or crystalline device to a stack of homogeneous layers and is the conceptual basis of standard solar-cell simulators, distinguishing it from two- or three-dimensional models that resolve lateral fingers, shunts, and microstructural inhomogeneities [4].
  • 2
  • 18 Sep 2026
Topic Review
Charge Carrier Dynamics
Charge carrier dynamics describes the generation, transport, and recombination of electrons and holes—the mobile charge carriers—in a semiconductor following an external excitation such as photon absorption or electrical injection [1]. After generation, excess carriers drift under internal electric fields and diffuse down concentration gradients, with mobilities and diffusion coefficients linked by the Einstein relation, until they are lost through recombination, quantified by the minority-carrier lifetime and the associated diffusion length [2]. Recombination may be radiative, non-radiative through trap states (Shockley–Read–Hall), or via Auger three-body processes, each characterized by a distinct rate and time scale [3]. In photoexcited materials, the temporal evolution of excess populations is commonly described by rate equations linking generation, drift, diffusion, and recombination, while transient optical probes follow the decay of photoluminescence or photoconductivity. The dynamic quantities—lifetimes, mobilities, diffusion lengths, and internal quantum yields—determine how efficiently photogenerated carriers are collected and therefore set the performance of photovoltaic, photoconductive, and other semiconductor devices [4].
  • 5
  • 18 Sep 2026
Topic Review
Surrounding Rock Deformation
Surrounding rock deformation refers to the time-dependent change in shape and position of the rock mass immediately adjacent to an underground excavation — such as a tunnel, roadway, cavern, or borehole — caused by the redistribution of in-situ stress after excavation [1]. Before excavation, the rock is in equilibrium under the virgin stress field; removal of material at the opening boundary causes stress concentration around the opening and induces displacements — radial convergence, wall displacement, roof sag, and floor heave — that may be elastic, elastoplastic, or viscoelastic depending on rock-mass quality, depth, and groundwater conditions [2]. The deformation field is governed by the stiffness, strength, and discontinuity geometry of the rock mass and is commonly analyzed using the convergence–confinement method, in which a ground-reaction curve relates radial displacement at the wall to the support pressure provided by linings, rock bolts, or shotcrete [3]. The term is distinguished from intact-rock deformation measured on laboratory specimens and from surface subsidence by its scale and by its location within the rock mass around the opening.
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  • 18 Sep 2026
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