Search Results (184)

Population-based bio-inspired metaheuristics are the dominant tools for tuning hybrid decomposition–deep-learning forecasters, yet their relative behavior on a common problem is rarely assessed with a leakage-free, physically meaningful protocol. We benchmark eight metaheuristics on the joint nine-dimensional hyperparameter optimization of a discrete-wavelet-transform bidirectional-LSTM (DWT–BiLSTM) architecture for short-term wind speed forecasting, using 409,152 hourly observations from eight meteorological stations. The set comprises six nature-inspired methods (Artificial Bee Colony, ABC; genetic algorithm, GA; Particle Swarm Optimization, PSO; Grey Wolf Optimizer, GWO; Hippopotamus Optimization, HO; and the Raindrop Optimizer) together with two recent metaphor-free or social variants (the Farthest-better Nearest-worse Optimizer, FNO; and the Tuckman Optimization Algorithm, TOA). A multi-stage protocol covers 30 independent runs per algorithm, a joint-versus-sequential comparison, a genuine rolling-origin out-of-sample evaluation, and component ablation. Friedman testing reveals significant differences (χ² = 49.76; p < 10⁻⁸), with the Grey Wolf Optimizer attaining the best mean rank (2.27) and Pareto-dominant run-time; ablation shows the DWT front-end is essential (Cohen’s d = 13.09) and bidirectionality negligible at the one-hour horizon (p = 0.674). Critically, evaluating forecasts in reconstructed physical units reveals that the per-component advantage does not persist: at the one-hour horizon the reconstructed forecast does not exceed a naive persistence baseline (skill ≈ −0.5 in m/s versus +0.44 in normalized component space), a discrepancy independent of decomposition leakage that we report transparently. This work thus contributes a rigorous, leakage-controlled bio-inspired benchmark and a cautionary evaluation methodology. Full article

This study provides the main performance estimates for new concepts, using flexible gasification operation modes, adaptable to prevailing market conditions, for the production of bio-synthetic natural gas (bio-SNG) and biochar from biogenic residues and waste, such as bark, straw, and Solid Recovered Fuel (SRF). Dedicated integrated process models were developed in Aspen Plus based on and validated against data from experimental campaigns in a gasification and gas cleaning pilot plant. Simulation runs show that the proposed concepts convert biomass to bio-SNG 10% more efficiently than the reference case, mainly due to the considerably reduced oxygen demand at the Autothermal Reformer (ATR) enabled by the improved catalyst. The co-production mode schemes showed promising results in terms of overall plant efficiency, at 76.5–78.2%, and total carbon utilisation, at 41–55.3%. The hybrid cases require an electrolyser with a power capacity almost 70% of the biomass thermal input to the gasifier, resulting in a total electricity consumption of up to 0.769 kWhe/kWh of biofuel. In return, they achieve over 50% utilisation of the carbon contained in the feedstock for biofuel production and a 70.1–76.5% total plant energy efficiency. Efficient biofuel and biochar production unlock negative emission potential, further strengthening the value of these flexible concepts. Full article

The role of internal combustion engines in future transport systems is expected to remain central, particularly in hard-to-abate sectors such as heavy-duty road transport and maritime applications. However, their decarbonization requires the adoption of low-carbon and renewable fuels. This review examines hydrogen, methane-based fuels, methanol, and ethanol for internal combustion engine applications using a pathway-based approach that integrates life-cycle assessment, technology readiness level, commercial readiness level, and engine-related considerations. The reviewed literature shows that the environmental performance of these fuels varies strongly depending on feedstock, production pathway, process configuration, and energy source. From a Well-to-Tank perspective, hydrogen pathways exhibit particularly large variability, ranging from around 3 gCO₂eq/MJ for wind-based electrolysis to around 230 g CO₂eq/MJ for coal gasification. Methane-based fuels range from around 16 gCO₂eq/MJ for fossil compressed and liquefied natural gas to negative values for waste- and manure-based biomethane. Methanol and ethanol also show substantial variability, with renewable, waste-derived, and bio-based pathways generally offering substantially lower life-cycle greenhouse gas (GHG) emissions than fossil-based routes. In the use phase, Tank-to-Wheel analysis shows that energy demand remains relatively similar across fuels, while differences in direct emissions are mainly related to fuel carbon content and other GHG species such as ${\mathrm{CH}}_4$ or ${\mathrm{H}}_2$ slip and combustion-related species such as ${\mathrm{N}}_2\mathrm{O}$. The Well-to-Wheel comparison for heavy-duty applications highlights that upstream fuel production pathways strongly influence overall performance, while use-phase contributions play a secondary role and mainly affect the final ranking when upstream emissions are comparable. Overall, the review shows that pathway selection is more influential than fuel identity itself, highlighting that effective decarbonization strategies should focus on pathway design and upstream fuel production rather than on fuel categories alone, and that renewable and bio-based pathways offer the greatest potential for achieving very low or near-zero life-cycle GHG emissions in internal combustion engine applications. Full article

The maritime sector accounts for approximately 3% of global greenhouse gas (GHG) emissions and faces binding decarbonization obligations under the International Maritime Organization’s (IMO) Net-Zero Framework and the FuelEU Maritime Regulation. Conventional marine fuels, including very low sulphur fuel oil (VLSFO) and liquefied natural gas (LNG), are insufficient to meet long-term regulatory intensity targets on a well-to-wake (WtW) lifecycle basis, creating an urgent need for credible fuel alternatives. This study investigates ethanol as a primary fuel for marine dual-fuel propulsion systems, assessed across four distinct production pathways, sugar beet, corn, sugarcane, and wheat straw, to determine its full decarbonization potential relative to VLSFO and LNG benchmarks. A simulation-based multi-dimensional evaluation framework is developed and applied, integrating dynamic operational simulation, energy analysis, environmental lifecycle modelling, and regulatory compliance assessment. The framework is calibrated against a high-resolution dataset from an active container ship, with scenario-specific engine data. While ethanol requires 39.1% more fuel mass than VLSFO due to its lower energy density, all four ethanol pathways deliver substantially superior WtW GHG reductions: from 50.2% (corn) to 76.9% (wheat straw), compared with 20.6% for LNG. All ethanol scenarios satisfy FuelEU compliance limits across the 2026–2045 horizon, with wheat straw ethanol achieving a GFI of 22.52 gCO₂e/MJ, compliant marginally with the 2040 IMO target. These findings demonstrate that bio-based ethanol, particularly from lignocellulosic feedstocks, is a technically viable and regulatorily superior alternative to LNG for maritime decarbonization, warranting accelerated research into production scale-up and bunkering infrastructure development. Full article

Traditional petroleum-based packaging suffers from pollution and functional limits, making it unsuitable for next-generation food systems. In contrast, bio-based smart packaging—combining renewable substrates with responsive components—transforms packaging from a passive shell into an active quality monitor and supply chain information node through three interconnected pillars: renewability, real-time responsiveness to freshness markers, and digital traceability. Market figures confirm this shift, with the smart food packaging sector projected to reach USD 48.97 billion by 2028 (CAGR 4.49% from 2023). This review covers recent progress in natural polymers (cellulose, chitosan, alginate, gelatin) and bio-based polyesters (PLA, PHA). Their multiscale structures enable tunable mechanical and barrier properties while serving as hosts for intelligent functions. Two functional directions stand out: active preservation (antimicrobial, antioxidant, gas-regulating, stimulus-controlled release) and intelligent sensing (colorimetric indicators, bio-based sensors, nano-amplified signals for real-time freshness monitoring). Beyond material functions, digital tools such as IoT and blockchain turn packaging into interactive data nodes, linking material intelligence with full traceability to enhance food safety and supply chain efficiency. Key challenges remain with long-term operational stability, production costs, scalable manufacturing, and life cycle assessments. Nevertheless, bio-based smart packaging is expected to evolve through biomimetic design, process innovation, and system-level integration toward adaptability, multifunctionality, and intelligence, ultimately supporting safer, more transparent, efficient, and sustainable food systems. Full article

Agricultural cold chain logistics is characterized by inherent challenges—product perishability, high carbon emissions, and stringent time windows—which are further exacerbated by dynamic disruptions. Existing methods suffer from slow adaptability, unstable multi-objective convergence, and severe cold-start issues. This work falls within the broad scope of biomimetics—the science of emulating nature’s time-tested strategies to solve complex engineering problems—and bio-inspired data-driven methods and their applications in engineering control, optimization, and artificial intelligence. The proposed H-MODRL framework embodies core biomimetic principles: the Genetic Algorithm (GA) mimics Darwinian natural selection and genetic inheritance, the Sparrow Search Algorithm (SSA) abstracts the cooperative foraging and anti-predation behaviors of sparrow populations in nature, and the Arrhenius-based freshness-decay model captures the biochemical kinetics governing perishable biological products. By synergistically integrating these biological evolution principles, swarm intelligence, and deep learning, the framework tackles real-world logistics complexity in a manner directly inspired by living systems. This study presents a well-organized hybrid optimization framework (H-MODRL) that couples a three-stage hybrid evolutionary mechanism, synergistically integrating heuristic warm-start, evolutionary policy guidance, and deep reinforcement learning decision-making. First, an improved genetic algorithm combined with the earliest deadline first strategy constructs a feasible initial population satisfying hard time-window constraints. Second, a large neighborhood search-enhanced chaotic sparrow search algorithm builds a high-quality elite guidance set for policy learning. Third, a physics-based multi-objective proximal policy optimization model embedded with Arrhenius equation-derived freshness-decay kinetics performs online decision-making. Experiments demonstrate that pre-computed all-pairs shortest paths and an O(1) hash-based dynamic-disruption indexing mechanism support fast online replanning. On heterogeneous simulated terrains based on real Chinese geospatial data, H-MODRL outperforms state-of-the-art algorithms across four objectives—logistics cost, carbon emissions, terminal freshness, and delivery time—while exhibiting compact, low-variance performance distributions, thereby validating its engineering robustness and practical value in complex agricultural cold chain environments. Full article

In recent years, animation-based systems for human-computer interaction have attracted increasing attention. This work proposes a hybrid framework that combines mathematical modeling and bio-inspired optimization algorithms to generate motion sequences from skeletal data. The framework takes as input a complete skeletal sequence corresponding to a given action and optimizes both the number of key poses and the parameters of a homotopy-based formulation to generate transitions between consecutive poses. A homotopy-based approach is used to compute transitions between selected key poses. The homotopy parameter $\lambda$ serves as an indicator of the completeness of the transition between pairs of key poses. Four nature-inspired optimization algorithms: Genetic Algorithm, Micro Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization were evaluated to determine the number of key poses and homotopy parameters that enable feasible motion generation. Dynamic Time Warping (DTW) is used as an external metric to assess the similarity between generated and reference sequences. It is important to note that Dynamic Time Warping (DTW) should be considered as a sequence similarity measure, as it does not explicitly evaluate perceptual realism or biomechanical plausibility. The framework was evaluated on 18 action sequences, demonstrating its ability to generate feasible motion transitions in 16 of the 18 evaluated actions when using PSO and MicroGA. For each pair of key poses, a fixed number of intermediate frames is generated to provide a uniform temporal discretization of the motion. The results suggest that homotopy-based methods provide a feasible approach for animation-based interaction systems. Full article

Plastic manufacturing depends heavily on petroleum-derived monomers like terephthalic acid, the main component of polyethylene terephthalate (PET). However, the depletion of fossil resources and increasing environmental concerns have heightened the need for sustainable alternatives. Lignocellulosic biomass has emerged as a promising resource due to its renewable, abundant, and eco-friendly nature. Understanding its chemical composition enables conversion of this biomass into platform chemicals, such as 2,5-furandicarboxylic acid (FDCA) and lactic acid, derived from cellulose and hemicellulose. These can be polymerized into bio-based plastics such as polyethylene furanoate (PEF), polylactic acid (PLA), and polyhydroxyalkanoates (PHAs), offering greener alternatives to fossil-based plastics. PEF features rigid furan rings that enhance thermal stability, mechanical strength, and barrier properties, and reduce gas permeability compared to PET. PLA is a renewable, biodegradable plastic widely used in packaging and medical applications. This review covers the chemical composition of lignocellulosic biomass cellulose, hemicellulose, and lignin, and various pretreatment strategies, chemical, physicochemical, and physical, to overcome biomass recalcitrance and improve conversion efficiency. It also highlights recent catalytic advances in transforming cellulosic carbohydrates into bio-based plastic precursors such as FDCA and lactic acid. Lastly, this review discusses polymerization pathways for producing PEF and PLA, emphasizing their role in reducing the environmental impact of polymer manufacturing and promoting green chemistry principles. Full article

The construction sector remains a major contributor to global energy consumption and greenhouse gas emissions. Heat loss through building envelopes plays a key role, especially in regions with long heating seasons. Hollow building blocks are widely used due to their low cost and structural simplicity, but their inadequate thermal insulation requires additional layers of insulation, increasing costs and complicating installation. The production of cement and traditional insulation materials is associated with a high carbon footprint and disposal issues, which conflict with sustainable development principles and decarbonization goals. In contrast to previous reviews that primarily address bio-based insulation in general building envelopes or focus on bioaggregates in concrete mixes, this paper specifically targets the application of biomaterials in hollow building blocks. It emphasizes how bio-based loose-fill and bound fillers interact with the peculiar thermo-fluid behavior of hollow cavities, including natural convection, conduction and radiation. The effects on thermal performance (thermal conductivity, U-value of walls) are analyzed, along with selected aspects of mechanical strength and durability. Gaps in long-term data on biodegradation are identified. Recommendations for selecting strategies depending on climate and design are offered, as well as directions for future research, including numerical modeling of thermal conditions. The results highlight the potential of biomodified blocks for creating energy-efficient and environmentally friendly wall systems. Full article

This study presents a fully integrated process for the flexible conversion of biogenic waste into synthetic natural gas (bio-SNG) and electricity centred on a 100 kWth dual concentric bubbling fluidised bed steam gasifier. The raw syngas is processed in a high-temperature gas cleaning section, and the resulting clean, H₂-rich syngas is directed to three alternative downstream configurations: (i) conventional methanation, (ii) enhanced methanation with external H₂ supplied by a reversible solid oxide cell (rSOC), and (iii) electricity generation via the same rSOC operating in fuel cell mode. The overall process is modelled in Aspen Plus, in which the gasification section is constrained by experimentally derived syngas data, while downstream units are described through thermodynamic and kinetics-based models. Methanation is simulated using a plug-flow reactor model based on validated kinetic expressions, while the rSOC operating in electrolysis and fuel cell mode is modelled using performance parameters of commercial stacks. A plant-wide heat integration strategy based on composite curve analysis is implemented to maximise internal heat recovery and minimise external utilities. The enhanced methanation configuration enables the production of bio-SNG with high methane content (up to 93.3 vol.% dry, N₂-free), with a yield 0.72 kg/kg_Biomass and a fuel efficiency of 70.1%. In electricity production mode, the system reaches an electrical efficiency of 43.1% with complete elimination of auxiliary fuel through thermal integration. These results demonstrate the capability of a single integrated plant to flexibly switch between fuel synthesis and power generation, enhancing adaptability to fluctuating electricity and methane market conditions while maintaining high efficiency. Full article

Fuel cell technologies are increasingly investigated as alternatives to conventional auxiliary diesel generators in order to enhance shipboard energy efficiency and reduce greenhouse gas emissions. This study presents a unified and uncertainty-driven system-level assessment of solid oxide fuel cell (SOFC) and proton exchange membrane fuel cell (PEMFC) systems operating as auxiliary power sources on a 200 m bulk carrier. Both technologies are evaluated under identical vessel characteristics, operating profiles, auxiliary load levels (360–600 kW), and cost assumptions, and are benchmarked directly against a conventional three–diesel-generator configuration. A modular numerical framework is developed to model propulsion–auxiliary interactions for ship speeds between 10 and 14 knots. SOFC systems are assessed using grey, bio-derived, and green natural gas pathways, while PEMFC systems are examined under grey, blue, and green hydrogen supply routes. Performance indicators include annual fuel consumption, carbon dioxide (CO₂) emission reduction, net present value (NPV), internal rate of return (IRR), payback period (PBP), and marginal abatement cost (MAC). Economic uncertainty is explicitly embedded in the framework through Monte Carlo simulation, where fuel prices (±20%) and capital costs are sampled across defined ranges, generating probabilistic distributions rather than single deterministic estimates. This uncertainty-centred approach enables assessment of robustness, downside risk, and probability of profitability. Results show that replacing a single operating 600 kW diesel generator with fuel cell systems reduces auxiliary fuel energy demand by 25–35% for SOFC and approximately 15–25% for PEMFC relative to the diesel benchmark. Annual CO₂ reductions range from 1.1 to 1.3 kt for SOFC systems and 1.8–2.8 kt for PEMFC configurations. Under grey fuel pathways, median NPVs reach approximately 2–4.5 M$ for SOFC and 9–17 M$ for PEMFC as load increases, with IRRs exceeding 15% and 30%, respectively. Transitional pathways exhibit narrower margins, while renewable pathways remain more sensitive to fuel price variability. The findings demonstrate that fuel pathway cost dominates lifecycle outcomes under uncertainty and that hydrogen-based PEMFC systems exhibit the strongest economic resilience within the examined market ranges. The framework provides structured, uncertainty-aware decision support and establishes a foundation for integration into model-based systems engineering (MBSE) environments for early stage ship energy system design. Full article

Waste from the wind power and textile industries poses major environmental challenges. While the textile industry is a significant global contributor to waste, producing around 92 million tons of waste annually, and greenhouse gas emissions, wind power, although one of the cleanest energy sources during operation, still generates waste and associated CO₂ emissions, particularly associated with the end-of-life decommissioning of turbine blades. This waste can be reused, combined with bio-based binders, to reduce the construction sector’s long-term environmental impact. The present work identifies research trends and gaps in the use of these waste materials, either individually or combined, for the development of thermal and acoustic insulation solutions for the construction sector, by means of a combined bibliometric and content analysis of Scopus and Web of Science documents from 2014 to 2025. The study focuses on bibliometric indicators and reports on physical properties (thermal conductivity, density, mechanical strength, and acoustic performance) of the resulting composites, including those produced with bio-binders. Additionally, a qualitative review of life cycle assessment studies indicates that bio-based and waste-derived insulation materials can significantly reduce environmental impacts compared with conventional mineral or petrochemical insulators. Results reveal growing scientific interest in this subject, highlighting an annual publication growth of 5.09%. They emphasize the performance of natural textile fibers in thermal and acoustic insulation, the mechanical capacity of synthetic fibers, and the semi-structural potential of fiberglass composites. Meanwhile, bio-binders improve the upcycling of textile waste; however, they reveal a significant research gap in the integration of wind turbine blade waste into insulation composites. No indexed studies were found that simultaneously combine textile waste, blade-derived fibers, and bio-based binders in a single insulation system, despite projected cumulative blade waste of 43 million tons by 2050. These findings advocate hybrid innovations and standardized assessments to drive circular economy and low-carbon building solutions. Full article

Synthetic natural gas (SNG) production from biomass residues represents a promising strategy to reduce greenhouse gas emissions and enhance energy security in regions with abundant agricultural waste. This study evaluates the thermodynamic performance of SNG synthesis from rice husk (RH) and empty fruit bunches (EFB) bio-oils, major residues in the department of Bolívar, Colombia. The process was simulated in Aspen Plus^®, integrating syngas data and methanation under equilibrium conditions at 320 °C and 30 bar, complemented by hydrogen injection via alkaline electrolysis to maintain an H₂/CO ratio above 3. Energy and exergy analyses were performed to quantify efficiencies and irreversibilities. Results indicate carbon conversion rates of 48.3% for EFB and 47.4% for RH, producing SNG with 96% CH₄ suitable for grid injection. Energy efficiencies reached 71.9% and 71.0%, while exergy efficiencies were 87.2% and 82.9%, respectively, aligning with or surpassing literature benchmarks. The main irreversibilities occurred in methanation and CO₂ removal, highlighting thermal integration and gas recycling as key improvement strategies. These findings demonstrate the potential of leveraging local biomass for clean energy production and support the development of Power-to-Gas systems in Colombia. Full article

The widespread use of conventional plastic mulch films in agriculture contributes significantly to soil pollution due to their non-biodegradable nature. This study explores the potential of novel bio-based mulch films composed of chitosan, carboxymethyl cellulose, and sodium alginate, formulated in different ratios (1:1 and 17:3), with or without enrichment with monoammonium phosphate (MAP), to serve as biodegradable films with potential nutrient-releasing functionality as alternatives to conventional plastics. A multi-analytical approach, including elemental and isotopic analysis (EA-IRMS), biodegradation assays, and pyrolysis–gas chromatography–mass spectrometry (Py-GC-MS), was employed to assess their chemical properties, degradation behavior, and environmental compatibility. The results demonstrated that the 1:1 films, both with and without MAP, achieved over 90% biodegradation within 120 days under controlled soil conditions, in agreement with international criteria for soil biodegradability. In contrast, the 17:3 films showed reduced degradation, especially without MAP enrichment, highlighting the influence of polymer composition on microbial degradation. Isotopic tracing confirmed MAP integration and revealed composition-dependent fractionation effects. Py-GC-MS provided structural fingerprints of film components and putatively annotated nitrogen-containing compounds indicative of chitosan presence. Overall, these results demonstrate that the 1:1 films can be considered viable, multifunctional, and soil-friendly alternatives to conventional plastic mulches for sustainable agriculture. Full article

Heavy-duty vehicles dominate global freight movement and primarily rely on fossil-derived diesel fuel. However, fluctuations in crude oil prices and evolving emissions regulations have prompted interest in alternative powertrains to enhance fleet energy resiliency. This study paired real-world operational data from a large commercial fleet with high-fidelity vehicle models to evaluate the potential for replacing diesel internal combustion engine (ICE) trucks with alternative powertrain architectures. The baseline vehicle for this analysis is a diesel-powered ICE truck. Alternatives include ICE trucks fueled by bio- and renewable diesel, compressed natural gas (CNG) or hydrogen (H₂), as well as plug-in hybrid (PHEV), fuel cell electric (FCEV), and battery electric vehicles (BEV). While most alternative powertrains resulted in some payload capacity loss, the overall fleetwide impact was negligible due to underutilized payload capacity for the specific fleet considered in this study. For sleeper cab trucks, CNG-powered trucks achieved the highest replacement potential, covering 85% of the fleet. In contrast, H₂ and BEV architectures could replace fewer than 10% and 1% of trucks, respectively. Day cab trucks, with shorter daily routes, showed higher replacement potential: 98% for CNG, 78% for H₂, and 34% for BEVs. However, achieving full fleet replacement would still require significant operational changes such as route reassignment and enroute refueling, along with considerable improvements to onboard energy storage capacity. Additionally, the higher total cost of ownership (TCO) for alternative powertrains remains a key challenge. This study also evaluated lifecycle impacts across various fuel sources, both fossil and bio-derived. Bio-derived synthetic diesel fuels emerged as a practical option for diesel displacement without disrupting operations. Conversely, H₂ and electrified powertrains provide limited lifecycle impacts under the current energy scenario. This analysis highlights the complexity of replacing diesel ICE trucks with admissible alternatives while balancing fleet resiliency, operational demands, and emissions goals. These results reflect a US-based fleet’s duty cycles, payloads, GVWR allowances, and an assumption of depot-only refueling/recharging. Applicability to other fleets and regions may differ based on differing routing practices or technical features such as battery swapping. Full article