Studies on the washing process have been mainly conducted experimentally, and only a few numerical approaches have been studied. Previous numerical studies on the washing process have focused on ...analyzing the dynamic behavior of laundry; however, no study has been reported on the detergency caused by the dynamic behavior of laundry. In this study, we predicted the detergency due to the dynamic behavior of the fabrics in a front-loading washing machine using discrete element method simulations and compared the prediction with that of the washing experiments. In addition, the agreement between the experimental and simulated detergencies was high, with a correlation coefficient of 99%. The detergency in the experiment was successfully predicted with power consumption of laundry calculated by the simulations. The lower detergency for larger amounts of fabric was mainly due to reduced normal contact. This study describes the first framework for front-loading washing machine simulations using the discrete element method.
For a washing machine, permanent-magnet (PM) motors are commonly used due to their superior efficiency, high torque-to-volume ratio, and so on. PM motor driving system with vector control scheme ...requires rotor-flux position information. Hall-effect position sensors are often used for that purpose because their volume is small and is cost effective compared with other types of position sensor such as an encoder, even though they have low resolution of position information. Generally, two low-resolution hall-effect sensors are employed to provide rotor flux position for cost reduction purpose and it means four resolutions per one electrical 360° rotation. The detected rotor-flux position by hall sensor signals is manipulated to change linearly by interpolation method. However, because of electrical and mechanical nonuniformity associated with hall sensors, the calculated or estimated position is not linearly changed. In other words, there exist bumps at the point where hall signal occurs even at the constant speed operation and it degrades control performance. To solve this problem, this paper proposes a novel scheme for bumpless position estimation. In addition, the proposed reduced-order observer does not use mechanical parameters such as inertia. The validity and effectiveness of the proposed algorithm are verified by experiments on a top-load washing machine vector-controlled with two Hall-effect sensors.
Effects of cyclic monensin feeding on in situ disappearance kinetics of low-quality forage (LQF; 4.9% CP) were evaluated. Ruminally cannulated steers (n = 12; Bos taurus; 260 kg BW) consuming LQF ...were randomly assigned to of 3 treatments in a completely randomized design: CON (0 mg∙animal-1∙day-1 monensin; Rumensin 90, Elanco Animal Health, Greenfield, IN), 2) MON (200 mg∙animal-1∙day-1 monensin), or 3) CYC (200 mg∙animal-1∙day-1 monensin for 4 d and 0 mg∙animal-1∙day-1 monensin for subsequent 4 d). Steers were fed dried distillers’ grains with solubles (1 kg∙animal-1∙day-1) for monensin inclusion. Four 28-d replicated cycles were used allowing 9 days for treatment adaptation, 4 days for sampling, and 4 days for withdrawal of monensin within the CYC treatment group. Low-quality forage samples were weighed into 0 × 20 cm polyester bags in replicates of four for each sampling hour. On d 0, all replicates were placed into the ventral area of the rumen and replicates were removed 0, 4, 8,6, 24, 48, and 72 hours post feeding. Upon removal, bags were rinsed in ice water, and frozen until final replicates were removed. Subsequently, bags were washed utilizing a commercial washing machine, dried at 55°C to a constant weight and dried residues were analyzed for DM. Ruminal in situ DM degradation data over time were fitted to the first-order exponential model with discrete lag using the NLIN procedure of SAS 9.4, then model parameters were compared with PROC GLIMMIX model to compare dietary treatments with period included as a random variable. There was no effect of treatment (P ≥ 0.22) on potentially degradable DM, rate of DM degradation, DM residue, DM lag, or wash loss of DM. Results are consistent with findings in the concurrent in vivo study conducted by Hook et al. (2022). Further evaluation of NDF degradability is required to determine a clear effect of cyclic monensin feeding on steers consuming an LQF.
Microplastics, particularly microfibers, are ubiquitous, found in aquatic (freshwater and marine) and terrestrial environments and within the food web worldwide. It is well-established that ...microplastics in the form of textile fibers enter the environment via washing machines and wastewater treatment effluent. Less is known about the release of microfibers from electric clothes dryers. In this study we measure microfiber emissions from home installed dryers at two different sites. At each site the distribution of fibers landing on the snow's surface outside dryer vents and the weight of lint in dryer exhaust exiting dryer vents were measured. Fibers from the pink polyester fleece blankets used in this study were found in plots throughout a 30ft (9.14m) radius from the dryer vents, with an average number across all plots of 404 #177; 192 (SD) (Site 1) and 1,169 #177; 606 (SD) (Site 2). The majority of the fibers collected were located within 5 ft (1.52m) of the vents. Averages of 35 #177; 16(SD)mg (Site 1) and 70 #177; 77 (SD)mg (Site 2) of lint from three consecutive dry cycles were collected from dryer vent exhaust. This study establishes that electric clothes dryers emit masses of microfiber directly into the environment. Microfiber emissions vary based on dryer type, age, vent installation and lint trap characteristics. Therefore, dryers should be included in discussions when considering strategies, policies and innovations to prevent and mitigate microfiber pollution.
In the industrial process, the safety and reliability of the mechanical system determine the quality of the product, and whether small faults can be diagnosed in time is the key to ensuring the safe ...operation of the system and restraining the deterioration of faults. In recent years, the data-driven fault diagnosis has attracted widespread attention in academia. However, the traditional data-driven fault diagnosis methods rely on the features extracted from expert systems, so that the effect of fault diagnosis is entirely reliant on how well the expert system can extract the features. This paper proposes a new fault diagnosis method based on AlexNet Convolutional neural network (CNN) from a data-driven perspective. Firstly, a new method for converting time-domain vibration signal into RGB image based on erosion operation (EOSTI) is proposed. Initially converted three-dimensional (3-D) images have relatively close structural elements and are difficult to identify. For such defects, the target separated RGB image is generated. Secondly, explore the classification accuracy of AlexNet to make it more suitable for fault classification of different bearing datasets. Finally, the proposed method which is tested on two datasets, including coal washing machine dataset, maintenance fault dataset, has achieved prediction accuracy of 99.43 % and 99.67 %, respectively. The results have been compared with other methods. The comparisons show the effectiveness and accuracy of the proposed approach. The result shows that this method is feasible in engineering practice.
Microplastics in the environment are a subject of intense research as they pose a potential threat to marine organisms. Plastic fibers from textiles have been indicated as a major source of this type ...of contaminant, entering the oceans via wastewater and diverse non-point sources. Their presence is also documented in terrestrial samples. In this study, the amount of microfibers shedding from synthetic textiles was measured for three materials (acrylic, nylon, polyester), knit using different gauges and techniques. All textiles were found to shed, but polyester fleece fabrics shed the greatest amounts, averaging 7360 fibers/m
−2
/L
−1
in one wash, compared with polyester fabrics which shed 87 fibers/m
−2
/L
−1
. We found that loose textile constructions shed more, as did worn fabrics, and high twist yarns are to be preferred for shed reduction. Since fiber from clothing is a potentially important source of microplastics, we suggest that smarter textile construction, prewashing and vacuum exhaustion at production sites, and use of more efficient filters in household washing machines could help mitigate this problem.
In horizontal-axis washing machines, the front gasket as well as the damping system are crucial owing to the possible collision of the tub with the housing during the transient period. However, most ...dynamic models for predicting tub motion focus on the steady state and consider only the suspension system without including the gasket. We conducted an experimental study to analyze the effect of the gasket on the transient motion of the tub. The results obtained indicate the necessity of implementing the gasket in the multibody model of a washing machine to accurately predict the tub behavior during this period. The gasket model is formed by a combination of Voigt elements. Stiffness parameters are determined using a load cell, and damping factors are estimated using a process that integrates Adams/View, Matlab optimization algorithms, and displacement measurements that are taken using accelerometers. A D-optimal design used to predict the effect of the gasket parameters reveals that the tub displacement is most sensitive to the changes in linear stiffness in the transversal direction. Finally, the model of the gasket provides a better approach for predicting the tub movement during resonance that can be used in the design phase to avoid tub collision.
Pro‐environmental consumption is necessary for sustainable development, but the sales of eco‐friendly products have been limited. In this regard, the present study analyses the failure factors of ...eco‐friendly product consumption activation from the consumer's perspective, specifically focusing on detergent‐free washing machines, which are representative innovative products of eco‐friendly home appliances. This study analyses: (1) the attitude‐behaviour gap that occurs in the consumer decision‐making process, and (2) the consumer preference with respect to the core attributes. A recursive model considering the decision‐making stage was constructed and a mixed logit model was utilized to analyse the preference for the core attributes. As a result, the product compatibility and transfer of expert information must be secured to reduce the attitude‐behaviour gap. Additionally, washing power is an important attribute for improving product saleability. The analysis framework of this study can be used to establish sustainable policies for activating eco‐friendly products.
Top loader washing machines are composed of an outer tub, inner drum, actuator and suspension with spring and dampers. When the drum rotates at a high speed, clothes are attached to the inner wall of ...the inner drum and the centrifugal force due to the unbalance mass makes a vibrating motion. In this study, the dynamic model of top loader washing machine was established to analyze the vibrating characteristics of the washing machine due to the unbalance mass effect and the mass effect of the fluid balancer. An integrated model of RecurDyn and Particleworks was made and used to analyze the dynamic behavior of the washing machine. The vibrating amount of the washing machine according to the position of the unbalance mass and its magnitude was analyzed. The accuracy of the dynamic model was verified by comparisons of the analysis results with experiments. By using the modal coordinates for the flexible multibody model, it was noted that the vibration of the top-loader washing machine was due to the deformation of the drum by unbalance masses.
Given the implications of microplastics contamination in aquatic ecosystems and information scarcity about microplastic abundances in estuarine sediments, this study aimed to quantify and describe ...the microplastics in the sublittoral sediments from Guanabara Bay. Sediment samples were collected at four sites and three months, microplastics were separated and classified according to type, color, size, and polymer composition. High abundances of microplastic (160 to 1000 items kg−1 or 4367 to 25,794 items m−2) occurred independent of area or period, indicating microplastics are widely spread in Guanabara Bay. The dominant microplastic in the sediment was the translucent polyester microfiber of <1 mm size; which is a secondary microplastic, possibly coming from washing machines wastes. The extremely high availability of microplastics in Guanabara Bay, compared to the majority of studies around the world, suggests high risk of contamination to benthic organisms and demersal fish, as they may be ingesting microplastics.
•The relevance of sampling microplastic in the sublittoral sediment•High microplastic abundance in a estuarine sediment,•Dominance of microplastic smaller than 1 mm•High abundance of polyester microfibers in the sediment
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