Search Results (46)

Precise control of the diesel oxidation catalyst (DOC) outlet temperature is critical for reliable diesel particulate filter (DPF) regenerations. This paper proposes a novel and composite control strategy for the DOC outlet temperature control based on a representative identified transfer function model, which requires only a nominal value of the input gain parameter. By integrating a PID-type sliding variable with a non-singular terminal sliding mode (TSM) manifold through the second-order sliding mode technique, the strategy provides a continuous and chattering-free control signal. A linear extended state observer (LESO) is designed for real-time estimation and compensation of the lumped total disturbances. Feedforward compensation (FFC) is also integrated to proactively counteract the effects of exhaust flow and inlet temperature variations, thereby reducing the burden on the LESO. The disturbance rejection control scheme is designed by combining the LESO, the chattering-free terminal sliding mode (CTSM), and the FFC. Its stability is proved by using the Lyapunov method. Comprehensive co-simulations conducted in a high-fidelity GT-Power/MATLAB environment demonstrated that the proposed control scheme achieves superior performance with respect to set-point tracking and disturbance rejection. This work provides an effective solution for robust temperature control in DPF regeneration processes. It can also be applied to other types of robust process control systems attributed to its ease of implementation. Full article

This study presents the metrological validation of encapsulated DS18B20 digital temperature sensors. Eight units were tested, and seven were analysed (sensor 8 was excluded owing to a systematic failure). The evaluation was performed using a standard comparison calibration, where T_ref was defined as the mean of two calibrated Pt-100 probes in a Julabo DYNEO DD 601F thermostatic bath, following the TH-001 procedure of the Spanish Centre of Metrology (CEM). Four validation tests were performed: Test 1 (E1, 20 to 75 °C), Test 2 (E2, 20 to 72 °C), and with an extended range, Test 3 (E3, −12 to 86 °C) and Test 4 (E4, −12 to 86 °C; repetition to assess reproducibility relative to E3), with 10 steady-state readings per setpoint. Erroneous readings were defined and removed (probe 3, Test 4), and set points without valid readings from probe 4 above 68 °C were excluded. Without data processing, the errors were consistent with the manufacturer’s stated ±0.5 °C, despite an inter-probe bias. Several correction models were evaluated (offset, affine linear, polynomial, and segmented); the probe-specific affine linear model provided the best overall compromise, reducing MAE (Mean Absolute Error) to 0.046 to 0.130 °C and RMSE (Root Mean Square Error) to 0.057 to 0.169 °C. The process uncertainty is dominated by the traceability of the Pt-100 probes and the effective nonuniformity of the isothermal volume, which limits the achievable accuracy. The results support the use of individually calibrated DS18B20 sensors for continuous monitoring, provided that the effective operating range is maintained. Full article

The temperature regulation of nonlinear continuous stirred tank reactor (CSTR) processes remains a challenging control problem due to strong nonlinearities, time-delay effects, and sensitivity to disturbances and parameter variations. Conventional proportional–integral–derivative (PID)-based control strategies often fail to provide the robustness and precision required under such conditions, motivating the use of more flexible controller structures and advanced optimization techniques. In this study, an enhanced joint-opposition artificial lemming algorithm (JOS-ALA) is proposed for the optimal tuning of a fractional-order PID (FOPID) controller applied to CSTR temperature control. The proposed JOS-ALA incorporates a joint opposite selection mechanism into the original ALA to improve population diversity, convergence stability, and resistance to local optima stagnation. A nonlinear CSTR model is linearized around a stable operating point, and the resulting model is employed for controller design and optimization. The FOPID controller parameters are tuned by minimizing a composite cost function that simultaneously accounts for tracking accuracy, overshoot suppression, and instantaneous error behavior. The effectiveness of the proposed approach is assessed through extensive simulation studies and benchmarked against state-of-the-art and high-performance metaheuristic optimizers, including ALA, electric eel foraging optimization (EEFO), linear population size reduction success-history based adaptive differential evolution (L-SHADE), and the improved artificial electric field algorithm (iAEFA). The benchmarking set is further extended with the success rate-based adaptive differential evolution variant (L-SRTDE) to broaden the comparative evaluation. Simulation results demonstrate that the JOS-ALA-based FOPID controller consistently achieves superior performance across multiple criteria. Specifically, it attains the lowest mean cost function value of 0.1959, eliminates overshoot, and yields a normalized steady-state error of 4.7290 × 10⁻⁴. In addition, faster transient response and improved robustness under external disturbances and measurement noise are observed when compared with competing methods. Statistical reliability of the observed performance differences is additionally examined using a Wilcoxon signed-rank test conducted over 25 independent runs. The resulting p-values confirm that the improvements achieved by the proposed approach are statistically significant at the 5% level across all pairwise algorithm comparisons. These findings indicate that the proposed JOS-ALA provides an effective and reliable optimization framework for high-precision temperature control in nonlinear CSTR systems and offers strong potential for broader application in complex process control problems. Full article

Additive manufacturing enables lightweight sandwich structures with complex cellular cores, but the selection of material and process settings typically involves trade-offs among mechanical performance, cost, and sustainability. This study proposes an integrated multi-criteria decision-making framework to identify the most suitable configuration for Fused Filament Fabrication (FFF) sandwich structures featuring a gyroid triply periodic minimal surface (TPMS) core. Eight alternatives are evaluated by combining two materials (PLA and PLA–Flax biocomposite) with two extrusion temperatures (200 °C and 220 °C) and two infill densities (20% and 30%). Mechanical performance is represented by flexural strength obtained from three-point bending tests reported in a previously published experimental campaign, while economic and environmental indicators are quantified through material cost and printing energy consumption, respectively. Criteria weights are derived using the Analytic Hierarchy Process (AHP) based on expert judgment and consistency-ratio verification, and the alternatives are ranked using the TOPSIS method. The results highlight a clear dominance of PLA-based configurations under the adopted weighting scheme, with PLA printed at 200 °C and 20% infill emerging as the best compromise solution. PLA–Flax options are penalized by higher material cost, higher printing-process energy demand, and lower flexural strength in the investigated conditions. The proposed AHP–TOPSIS workflow supports transparent, data-driven selection of AM process–material combinations for gyroid sandwich structures, and it can be readily extended by including additional sustainability metrics (e.g., CO₂-equivalent) and application-specific constraints. A sensitivity analysis under alternative weighting scenarios further confirms the robustness of the obtained ranking. Full article

Hot fresh pork is highly preferred by Chinese consumers for its desirable flavor and color. However, its quality deteriorates rapidly during ambient-temperature transportation, leading to unappealing meat color and shortened shelf life. This study investigated the effects of different transportation temperature setpoints (5 °C, 10 °C, 15 °C Setpoint groups, and ambient temperature) on pork carcass quality. Transportation at the lower setpoints (5 °C, 10 °C) reduced carcass center temperature, attenuated pH decline, minimized cooking and drip losses, suppressed microbial proliferation, and curtailed TVB-N accumulation (p < 0.05). These conditions also shortened the duration of high temperatures in vehicles, decelerated glycogenolysis, and moderated energy metabolism, collectively preserving meat quality. Regarding color, 5 °C Setpoint group inhibited myoglobin oxidation, yielding lower oxygenated myoglobin content and reduced a* values compared with 10 °C Setpoint group over 150 km (p < 0.05). High-throughput sequencing revealed that temperature setpoint transportation significantly influenced bacterial community succession, with highly similar profiles between the 5 °C and 10 °C Setpoint groups, yet clear divergence from the ambient control. Therefore, transportation at 10 °C Setpoint represents a balanced approach to preserving color, delaying spoilage, and extending shelf life. Full article

In the framework of high temperature components, the need to evaluate the accumulated creep damage during service life is fundamental to extend the life of components which are currently deemed as scrap as per design intent. Thus, the life assessment of Ni-based superalloys could be performed in relation to the accumulated creep deformation which represents the limiting factor for serviced components. Despite the different microstructural changes that occur in service life, this work focuses on the possibility to evaluate the material strain by means of electron backscattered diffraction (EBSD). The key point is the identification of the correlation between geometrically necessary dislocation (GND) density derived from EBSD analyses and the reached creep strain for a single crystal Ni-based superalloy. However, the results of GND density are affected by the settings’ parameters adopted to perform the analysis by the magnification level and the step size. These two parameters have been optimized by analyzing specimens from interrupted creep tests at strain levels between 0.5% and 10%, in the temperature range between 850 °C and 1000 °C. Full article

To improve the accuracy and robustness of lithium-ion battery state of charge (SOC) estimation, this paper proposes a generalized mixture maximum correlation-entropy criterion-based adaptive extended Kalman filter (GMMCC-AEKF) algorithm, addressing the performance degradation of the traditional extended Kalman filter (EKF) under non-Gaussian noise and inaccurate initial conditions. Based on the GMMCC theory, the proposed algorithm introduces an adaptive mechanism and employs two generalized Gaussian kernels to construct a mixed kernel function, thereby formulating the generalized mixture correlation-entropy criterion. This enhances the algorithm’s adaptability to complex non-Gaussian noise. Simultaneously, by incorporating adaptive filtering concepts, the state and measurement covariance matrices are dynamically adjusted to improve stability under varying noise intensities and environmental conditions. Furthermore, the use of statistical linearization and fixed-point iteration techniques effectively improves both the convergence behavior and the accuracy of nonlinear system estimation. To investigate the effectiveness of the suggested method, experiments for SOC estimation were implemented using two lithium-ion cells featuring distinct rated capacities. These tests employed both dynamic stress test (DST) and federal test procedure (FTP) profiles under three representative temperature settings: 40 °C, 25 °C, and 10 °C. The experimental findings prove that when exposed to non-Gaussian noise, the GMMCC-AEKF algorithm consistently outperforms both the traditional EKF and the generalized mixture maximum correlation-entropy-based extended Kalman filter (GMMCC-EKF) under various test conditions. Specifically, under the 25 °C DST profile, GMMCC-AEKF improves estimation accuracy by 86.54% and 10.47% over EKF and GMMCC-EKF, respectively, for the No. 1 battery. Under the FTP profile for the No. 2 battery, it achieves improvements of 55.89% and 28.61%, respectively. Even under extreme temperatures (10 °C, 40 °C), GMMCC-AEKF maintains high accuracy and stable convergence, and the algorithm demonstrates rapid convergence to the true SOC value. In summary, the GMMCC-AEKF confirms excellent estimation accuracy under various temperatures and non-Gaussian noise conditions, contributing a practical approach for accurate SOC estimation in power battery systems. Full article

Low-concentration trichloroethylene (TCE) and tetrachloroethylene (PCE) indoors pose a significant threat to human health due to their potent carcinogenic properties. However, existing research has predominantly focused on high-concentration scenarios in industrial settings, offering limited guidance for indoor air purification. This study investigated the adsorption mechanisms and performance regulation of coconut shell activated carbon for TCE/PCE through experimental analysis, molecular simulations, and dynamic modeling. Experimental results demonstrated that PCE, characterized by its non-polar nature and high boiling point, exhibited a substantially higher adsorption capacity than TCE. Increased humidity induced competitive adsorption between water molecules and pollutants, reducing the adsorption capacity of PCE by approximately 30%. Molecular simulations validated that water molecules occupied the active sites of oxygen-containing functional groups and pores, impeding the diffusion of TCE/PCE, while the non-polar surface of activated carbon preferentially adsorbs PCE. A dynamic prediction model developed in this study accurately forecasted breakthrough curves under varying pollutant concentrations, temperatures, humidities, and air velocities and quantified the service life of activated carbon. Response surface methodology revealed that controlling inlet concentrations (TCE < 7 ppb, PCE < 30 ppb), air velocity (<1 m/s), humidity (<50%), and temperature (<25 °C) can extend the service life of activated carbon to 3–5 months. Full article

This study evaluates indoor thermal comfort and the energy performance of HVAC control strategies in the Congo Zone of a zoological facility located in Poland. The main objective in this zone is to maintain adequate relative humidity, which is more critical for plants and animals than the indoor air temperature range. Long-term measurements were carried out to determine the variation of air system heat transfer as a function of outdoor air temperature. To determine the energy demand for heating, cooling, and air transport, eight control algorithms were analysed, each differing in a single detail but potentially affecting overall energy use and thermal comfort. The algorithms combined the following features: maintaining a constant supply or indoor air temperature; operating with a constant or modulated recirculation damper position; maintaining a constant or variable airflow (CAV or VAV); operating within the normal setpoint range or with an extended range of 1 °C; controlling temperature only or both temperature and humidity; and utilising or not utilising free cooling. The control algorithm operating in the facility maintained indoor humidity within acceptable limits for 98% of the year but failed to meet temperature requirements for 28% of the time. Refined strategies achieved energy savings of up to 74% in fan power and 80% in cooling demand, though often at the cost of reduced humidity control. Full article

The temperature and polarization anisotropies of the cosmic microwave background (CMB) as measured today can offer key insights into the topology of the early universe prior to inflation, for example by discriminating between flat and warped geometries. In this paper, we focus on a Kaluza–Klein model with an extra spatial dimension that compactifies at the Grand Unified Theory (GUT) epoch, subject to mixed Neumann/Dirichlet boundary conditions at fixed points. As a consequence, a set of Infrared (IR) cutoffs emerges in both the scalar and tensor spectra, leading to observable consequences in the CMB. We examine the possible signatures of such a topology in detail, particularly in relation to the even–odd parity imbalance already reported by the COBE, WMAP and Planck missions in the temperature angular correlations. Furthermore, we extend our analysis to the existing Planck E-mode polarization data and to the high-precision B-mode polarization measurements expected from the forthcoming LiteBIRD mission. Full article

This study investigates the performance improvement of asphalt binders through the incorporation of two polymers, polyvinyl chloride (PVC) and styrene–butadiene–styrene (SBS), with asphalt grade (60–70), to address the growing demand for durable and climate-resilient pavement materials, particularly in areas exposed to high temperatures like Iraq. The main objective is to improve the mechanical characteristics, thermal stability, and workability of typical asphalt mixtures to extend pavement lifespan and lessen maintenance costs. A thorough set of rheological, physical, morphological, and workability tests was performed on asphalt binders modified with varying content of PVC (3%, 5%, 7%, and 9%) and SBS (3%, 4%, and 5%). The significance of this research lies in optimizing binder formulations to enhance resistance to deformation and failure modes such as rutting and thermal cracking, which are common in extreme climates. The results indicate that PVC enhances performance grade (PG), softening point, and viscosity, although higher contents (7% and 9%) exceeded penetration grade specifications. SBS-modified binders demonstrated marked improvements in softening point, viscosity, and rutting resistance, with PG values increasing from PG64-x (unmodified) to PG82-x at 5% SBS. Fluorescence microscopy confirmed optimal polymer dispersion at 5% concentration for both SBS and PVC, ensuring compatibility with the base asphalt. Workability testing revealed that SBS-modified mixtures exhibited higher torque requirements, indicating reduced workability compared to both PVC-modified and unmodified binders. These findings offer valuable insights for the design of high-performance asphalt mixtures suitable for hot-climate applications and contribute to the development of more durable and cost-effective road infrastructure. Full article

The ammonia energy ratio (AER) is a critical parameter influencing the performance of ammonia/diesel dual-fuel engines. In this study, a numerical simulation was conducted based on a high-pressure dual-fuel (HPDF) direct injection ammonia/diesel engine to investigate the impact of the AER on combustion and emissions under two distinct combustion modes. By adjusting the ammonia start of injection timing (ASOI), the combustion mode was transitioned from diffusion combustion (HPDF1) to partially premixed combustion (HPDF2). The results show that under the HPDF1 mode, a three-stage heat release pattern is observed, and the evolution curves of NO and NO₂ exhibit fluctuations similar to the heat release process. As the AER increases, the second heat release stage is suppressed, the high-temperature region narrows, the ignition delay is extended, and the CA10–CA50 interval shortens, leading to a higher maximum pressure rise rate (MPRR) at a high AER. Conversely, in the HPDF2 mode, the combustion process is characterized by a two-stage heat release. With an increasing AER, the high-temperature region expands, the ignition delay and CA10–CA50 interval are prolonged, while the CA50–CA90 interval shortens, and the MPRR becomes the lowest at a high AER. For both combustion modes, total greenhouse gas (GHG) emissions decrease with an increasing AER. However, in the HPDF2 mode with an AER = 95%, N₂O accounts for up to 78% of the total GHG emissions. Additionally, a trade-off relationship exists between NOx emissions and indicated thermal efficiency (ITE). When the ASOI is set to −8°CA ATDC, the engine operates in a transitional combustion mode between HPDF1 and HPDF2. At this point, setting the AER to 95% effectively mitigates the trade-off, achieving an ITE of 53.56% with NOx emissions as low as 578 ppm. Full article

Fruits are perishable fresh products with a short shelf life after harvesting. Perishable foods and their shelf lives are directly related to the temperature at which they are stored. Refrigeration is therefore essential in the conservation of fruits, as it allows the temperature to be lowered, helping to delay microbial, physiological, and chemical changes. This work aimed to compare the thermal behaviors of alveoli with different phase change materials (PCMs) placed inside a modular packaging developed for the transport and storage of fruits. The cooling tests were carried out inside a cold storage chamber with the set-point programmed to 2 °C. To simulate the placement in packages exposed to the store environment, heating tests were carried out while the chamber door was opened and the packaging was exposed to external environmental conditions. The phase change materials tested were RT2HC, RT5HC, and RT8HC. The temperature variation in the tests during cooling and heating proved that the new type of alveoli with PCM inside the fruit transport packaging is extremely important, as it can extend the useful life of the fruits after they are removed from the cold chamber, managing to maintain adequate conservation conditions for longer in contact with room temperature. The phase change material RT8HC was the one that showed the best results overall, managing to maintain the temperature of the fruit inside the packaging at a temperature below 10 °C for up to eight hours after being exposed to ambient conditions of 20 °C. Full article

Isothermal amplification (IA) techniques like rolling circle amplification (RCA) and loop-mediated isothermal amplification (LAMP) have gained significant attention in recent years due to their ability to rapidly amplify DNA or RNA targets at a constant temperature without the need for complex thermal cycling equipment. Such technologies, combined with colorimetric systems rendering visual confirmation of the amplification event, are ideal for the development of point-of-need detection methods suitable for field settings where access to specialized laboratory equipment is limited. The utility of these technologies, thus far limited to DNA and RNA targets, could be broadened to a wide range of targets by using aptamers. Composed of DNA or RNA themselves, aptamers can bind to substances, including proteins, metabolites, and inorganic substances. Their nucleic acid nature can potentially allow them to serve as a bridge, extending the reach of DNA/RNA-centric technologies to the broader molecular world. Indeed, the change in aptamer conformation occurring during ligand interaction can be used to elaborate ligand-responding RCA or LAMP templates. By using an existing aptamer targeting SARS-CoV-2 Spike protein as a model, we explored the possibility of establishing ligand-responsive IA systems. Our study used aptamers with simple sequence modifications as templates in LAMP assays and hyperbranched RCA (HRCA) by exploiting the dynamic nature of the model aptamer to trigger these IA systems. Importantly, our work uniquely demonstrates that this aptamer’s dynamic response to ligand binding can regulate both RCA and LAMP processes. This novel approach of using aptamer conformational changes to trigger LAMP paves the way for new aptamer-based detection assays. Our system detects 50 nM of Spike protein, with LAMP occurring within 30 min in the presence of Spike. The colorimetric readout showed clear results, allowing for the detection of Spike protein presence. Full article

In open and shared workplaces, like co-working spaces or educational studios, thermal preferences vary widely among occupants. With the rise of flexible organizational workplace strategies, the challenge lies in balancing optimum, efficient temperature setpoints with maintaining occupants’ comfort. A potential solution involves a deeper understanding of variations in indoor climate and building occupants’ decision-making and preferences. This paper explores how an Occupant-Centric Digital Twin (OCDT) might address this by mapping indoor microclimates through a grid of IoT temperature sensors in real time. A large-screen display is utilized to present and visualize these data in an open workplace. The goal is to enhance awareness and provide agency for occupants to identify zones that align with their individual thermal preferences. A mixed-method occupant study (N = 27) was conducted to validate the approach. Exposure to the OCDT display resulted in higher thermal satisfaction among participants (p-value = 1.269 × 10⁻⁵, 0.05 significance level). The novelty of OCDT lies in extending the use of digital twin technology from facility managers to occupants, by granting them the agency to address comfort issues even in buildings where they lack direct control over the thermostat. This approach paves the way for a future where occupants in open workspaces can make informed decisions about where to work and how to achieve thermal comfort in those choices. Full article