This study focuses on converting underutilized or discarded sawdust from Eucalyptus grandis (EG) and Pinus elliottii (PE), along with roasting chicken oil (RCO) and chicken visceral oil (CVO), into ...alternative briquettes. Employing heuristic methods and branch-and-bound techniques, 27 experiments were conducted based on a central composite design (CCD), including two central point repetitions. The energy density (ED) of the briquettes was evaluated immediately after production (EDi) and three months later (EDf). The higher heating value (HHV), thermogravimetric analysis (TGA) with its first derivative, and cost of each briquette were also characterized. Increasing chicken oil content improved HHV, initial ED, reduced ash content, and enhanced thermal degradation performance. However, exceeding 15% oil content caused wastage during pressing. Excessive CVO use is cost-prohibitive unless produced by the poultry industry. The optimal briquette was obtained in experiment 9 with 21.25% EG, 63.75% PE, 3.75% CVO, and 11.25% RCO by mass. Structural neighbors were identified based on this composition. Sawdust type and particle size had minimal impact on the results.
Specific energy consumption (SEC) also called energy intensity is one of the important aspects for lumber sawing sawmills since it represents the energy efficiency of the sawmill. Production, ...process, and energy data were gathered by visiting five sawmills out of which three sawmills had single sawing lines and two sawmills had double sawing lines. Sawmills with single and double sawing lines were selected in order to cover the different sawmill configurations. Data from sawmills 1, 2, 4, and 5 was used to develop an estimation model to estimate SEC of sawmill 3 based on the product, process, and system parameters. The independent variables that were included in the model were species, lumber sizes for the product, sawing time, maintenance schedule for the process, and motor horsepower, availability of resaw, and production line configuration for the system. Energy consumption of a motor on the demand side mainly depends on its capacity, operating hours, and load factor/efficiency ratio, and model 2 in this paper estimated SEC of a new sawmill from the product, process, and system parameters which represented the load factor/efficiency ratio when capacity and operating hours were known in the new sawmill. The product, process, and system parameters in model 3 represented motor capacity also along with the load factor/efficiency ratio and estimated SEC of a new sawmill. The developed regression models can be used to predict the sawing energy consumption of a new sawmill with reasonable accuracy.
This paper addresses a multi-period, multi-product sawmill production planning problem where the yields of processes are random variables due to non-homogeneous quality of raw materials (logs). In ...order to determine the production plans with robust customer service level, robust optimization approach is applied. Two robust optimization models with different variability measures are proposed, which can be selected based on the tradeoff between the expected backorder/inventory cost and the decision maker risk aversion level about the variability of customer service level. The implementation results of the proposed approach for a realistic-scale sawmill example highlights the significance of using robust optimization in generating more robust production plans in the uncertain environments compared with stochastic programming.
This study employs Thermogravimetric Analysis (TGA) to explore co-pyrolysis potential using polystyrene (PS) and coconut sawmill residue (CSR) for liquid fuel production. Two distinct degradation ...stages are observed in CSR-PS blends, mirroring pure CSR samples: the initial phase (200-400°C) decomposes biomass components, while the second stage (400-550°C) targets the synthetic polymer PS within CSR-PS blends. Analyzing thermal degradation parameters reveals insights. 100% PS exhibits the highest weight loss and activation energy, highlighting PS's formidable decomposition. Conversely, 100% CSR shows the lowest weight loss and activation energy due to its organic composition. Artificial Neural Network (ANN) modeling indicates varying correlation accuracies for different blend compositions. Surprisingly, 100% PS exhibits lower correlation accuracy in predicting weight loss compared to the 80% PS blend, which achieves a perfect correlation. Conversely, 100% CSR, with simpler decomposition, has the lowest correlation accuracy. These findings illuminate the complex thermal behavior of CSR-PS blends, emphasizing the distinct degradation characteristics of PS and CSR. Implications extend to material applications and disposal strategies, emphasizing tailored approaches based on blend compositions and thermal profiles. This research advances co-pyrolysis as a sustainable avenue for liquid fuel production, providing insights for future research and practical applications.
River water quality and habitats are degraded by thermal pollution from urban areas caused by warm surface runoff, lack of riparian forests, and impervious channels that transfer heat and block cool ...subsurface flows. This study updates the i-Tree Cool River model to simulate restoration of these processes to reverse the urban river syndrome, while using the HEC-RAS model water surface profiles needed for flood hazard analysis in restoration planning. The new model was tested in a mountain river within the New York City drinking water supply area (Sawmill, SM, Creek), and then used for base case and restoration scenarios on the 17.5 km reach of the Los Angeles (LA) River where a multi-million dollar riverine restoration project is planned. The model simulated the LA River average temperature in the base case decreased from 29.5 °C by 0.3 °C when warm surface inflows were converted to cooler groundwater inflows by terrestrial green infrastructure; by 0.7 °C when subsurface hyporheic exchange was increased by removal of armoring and installation of riffle-pool bedforms; by 3.6 °C when riparian forests shaded the river; and by 6.4 °C when floodplain forests were added to riparian forests to cool surface reservoirs and local air temperatures. Applying all four restoration treatments lowered river temperature by 7.2 °C. The simulated decreases in river temperature lead to increased saturated dissolved oxygen levels, reaching 8.7 mg/L, up from the 7.6 mg/L in the base case scenario, providing improved fish habitat and reducing eutrophication and hypoxic zones. This study evaluating the performance of environmental management scenarios could help managers control the thermal pollution in rivers.
•i-Tree Cool River was updated to capture thermal impact of river basin restoration on river flows estimated by the HEC-RAS.•The simulated Los Angeles River temperature was lowered by 3% by green infrastructure and riffle-pool bedforms.•When riparian shading was added to other two restoration scenarios, the simulated LA River temperature was lowered by 14%.•Floodplain forest expansion with other restoration scenarios, lowered the simulated LA River. temperature was by 25%.
•Vietnam aims to increase the supply of certified wood to industry.•The study compares financial returns from certified & non-certified forest products.•Returns from certified timber are higher for ...both growers & for sawmill businesses.•But the benefits to sawmill owner is higher than that of the growers.•If full cost of certification is applied to growers, it is not attractive to them.
The demand for forest products is growing and plantation forests are supplying an increasing proportion of wood to industry. There are also increasing market requirements to demonstrate the sustainability of timber supply. Vietnam has some 3.9Mha of plantation forests, 44% of which is on short-rotations managed by smallholders. More than 80 percent of the harvested volume from the plantation forests is used for woodchip production to serve domestic and international markets. The Vietnam Government has goals to increase the domestic supply of suitable wood for furniture production to international markets by increasing the supply of larger logs grown in plantations and the supply of certified wood to industry. However, it is not clear that these objectives will necessarily benefit growers and processors. This study compared financial returns from certified and non-certified forest products for: (1) growers with 10-year rotation acacia plantations; and (2) a furniture processing business (battens for chair and table) in Quang Tri Province, Central Vietnam. The data were collected from smallholder tree growers and a sawmilling company, triangulated with and supplemented by formal and informal interviews with other stakeholders. Currently, much of the cost of certification is met by external aid donors. Results showed that net returns from both certified and non-certified timber products are positive for both actors and are higher from certified timber production than non-certified timber production. When the full costs of certification are included, the benefits to growers of certification are much reduced and potentially negative unless the fixed costs can be spread over a large group of growers. A minimum of group with 3000ha may be required to make certification cost effective. In recent years, the price difference between the certified and non-certified logs is narrowing and this may discourage farmers from attaining certification. For the sawmiller, the benefit of certified timber production is greater. It would be in their interests to increase prices paid to growers for certified logs. Government policy measures to support certification should include consideration of who bears the cost, support for aggregation of smallholder growers and improved communication in timber supply chains.
Resumen Los objetivos de esta investigación fueron: (a) Conocer la distribución de las especies de pino aserradas y estimar una distribución de clases de calidad visual de las trozas, (b) Determinar ...la frecuencia de rendimiento de aserrado y evaluar el efecto del diámetro menor con corteza y la conicidad de la troza en el mismo, y (c) Estimar el rendimiento volumétrico y la distribución de productos aserrados en el suroeste del estado de Chihuahua. Se integraron en el proceso de aserrado 182 trozas a las que se les identificó la especie, se evaluó su calidad, el rendimiento por categoría de diámetro menor y la conicidad con corteza. Se calculó el rendimiento volumétrico de los espesores, anchos, largos y calidad de madera aserrada obtenida de 1 348 trozas. Las variables se evaluaron con pruebas de normalidad, análisis de varianza y pruebas de correlación con la finalidad de identificar diferencias significativas (p<0.05). Se concluyó que Pinus arizonica es la principal especie que se transforma, al representar 45.70 % del total; la madera en rollo de calidad 5 es la más común con 27.67 % del total; el rendimiento de aserrado más frecuente es de 50.00 %; la categoría de diámetro y la conicidad de la troza son variables que definen el rendimiento de aserrado. Las principales dimensiones que se generan en el sureste del estado de Chihuahua son de 7/8” de espesor, 8” de ancho y 16´ de largo.
•Exploration of active learning concepts with real industrial data in a stream-based setting.•Coupling of a digital simulation tool and a machine learning metamodel through an Active learning ...approach.•Trad-off between the prediction quality of ML and the sawing simulator usage computational cost using a simulation budget concept.•Careful selection of data to continuously train the ML metamodel, in accordance with the smart data paradigm.
Although digital simulations are becoming increasingly important in the industrial world owing to the transition toward Industry 4.0, as well as the development of digital twin technologies, they have become increasingly computationally intensive. Many authors have proposed the use of machine learning (ML) metamodels to alleviate this cost and take advantage of the enormous amount of data that are currently available in industry. In an industrial context, it is necessary to continuously train predictive models integrated into decision support systems to ensure the consistency of their prediction quality over time. This led the authors to investigate active learning (AL) concepts in the particular context of the sawmilling industry. In this paper, a method based on AL is proposed to combine simulation and an ML metamodel that is trained incrementally using only selected data (smart data). A case study based on the sawmilling industry and experiments are shown, the results of which prove the possible advantages of this approach.
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