Performance Of Filter Research Articles

Speech Enhancement Algorithm Based on Microphone Array and Lightweight CRN for Hearing Aid

To address the performance and computational complexity issues in speech enhancement for hearing aids, a speech enhancement algorithm based on a microphone array and a lightweight two-stage convolutional recurrent network (CRN) is proposed. The algorithm consists of two main modules: a beamforming module and a post-filtering module. The beamforming module utilizes directional features and a complex time-frequency long short-term memory (CFT-LSTM) network to extract local representations and perform spatial filtering. The post-filtering module uses analogous encoding and two symmetric decoding structures, with stacked CFT-LSTM blocks in between. It further reduces residual noise and improves filtering performance by passing spatial information through an inter-channel masking module. Experimental results show that this algorithm outperforms existing methods on the generated hearing aid dataset and the CHIME-3 dataset, with fewer parameters and lower model complexity, making it suitable for hearing aid scenarios with limited computational resources.

A unified framework for the analysis of accuracy and stability of a class of approximate Gaussian filters for the Navier–Stokes equations

Abstract Bayesian state estimation of a dynamical system utilising a stream of noisy measurements is important in many geophysical and engineering applications. In these cases, nonlinearities, high (or infinite) dimensionality of the state space, and sparse observations pose key challenges for deriving efficient and accurate data assimilation (DA) techniques. A number of DA algorithms used commonly in practice, such as the Ensemble Kalman Filter (EnKF) or Ensemble Square Root Kalman Filter (EnSRKF), suffer from serious drawbacks such as catastrophic filter divergence and filter instability. The analysis of stability and accuracy of these DA schemes has thus far focused either on finite-dimensional dynamics, or on complete observations in case of infinite-dimensional dissipative systems. We develop a unified framework for the analysis of several well-known and empirically efficient DA techniques derived from various Gaussian approximations of the Bayesian filtering schemes for geophysical-type dissipative dynamics with quadratic nonlinearities. We establish rigorous results on (time-asymptotic) accuracy and stability of these algorithms with general covariance and observation operators. The accuracy and stability results for EnKF and EnSRKF for dissipative PDEs are, to the best of our knowledge, completely new in this general setting. It turns out that a hitherto unexploited cancellation property involving the ensemble covariance and observation operators and the concept of covariance localization in conjunction with covariance inflation play a pivotal role in the accuracy and stability for EnKF and EnSRKF. Our approach also elucidates the links, via determining functionals, between the approximate-Bayesian and control-theoretic approaches to DA. We consider the ‘model’ dynamics governed by the two-dimensional incompressible Navier–Stokes equations (NSEs) and observations given by noisy measurements of averaged volume elements or spectral/modal observations of the velocity field. In this setup, several continuous-time DA techniques, namely the so-called 3DVar, EnKF and EnSRKF reduce to a stochastically forced NSEs. For the first time, we derive conditions for accuracy and stability of EnKF and EnSRKF. The derived bounds are given for the limit supremum of the expected value of the L 2 norm and of the H 1 Sobolev norm of the difference between the approximating solution and the actual solution as the time tends to infinity. Moreover, our analysis reveals an interplay between the resolution of the observations (roughly, the ‘richness’ of the observation space) associated with the observation operator underlying the DA algorithms and covariance inflation and localization which are employed in practice for improved filter performance.

LCL APF control strategy based on model predictive control

In order to further control harmonic current in distribution network, a LCL APF control strategy based on model predictive control is proposed. Firstly, APF mathematical model is established. Then, a multi-objective optimization model predictive control strategy (MPC) is proposed, which comprehensively considers the performance of AC side and DC side of APF. This strategy solves the delay problem existing in the existing MPC strategy: while improving the performance of APF, there is no need to set weight factor; Then, Kalman filter is used to predict the inverter current, thus simplifying the APF measurement system. Finally, the simulation results show that the proposed control strategy can simplify the measurement system and make APF have stronger harmonic suppression ability when it only participates in power conversion and better active filter performance when it participates in harmonic control.

Coalescence performance of Janus filter for the removal of oil mist

The wettability has an important effect on coalescence performance of filter. In this paper, we utilized a commercial glass fiber filter as the substrate to prepared the Janus filter through dip-coating and electrospraying. The Janus filter exhibited a remarkable reduction in pressure drop, with only 2.8 kPa of wet pressure drop compared to 6.1 kPa for the original filter and 5.4 kPa for the oleophilic filter. Notably, the coating depth played a critical role in enhancing the coalescence performance of the Janus filter. Furthermore, when placing the Janus filter in reverse direction, its quality factor increased by 2.87 times, highlighting that orientation is an essential factor for coalescence performance of Janus filters. The results indicate great potential in the application of Janus filters for coalescence filtration.

Swelling problems in immobilized filler: an improvement method and comparative study of the effect of different fillers on biotrickling filters.

Immobilized fillers have been increasingly utilized in biotrickling filters (BTFs) due to their positive impact on shock load resistance and recovery performance. However, due to the inherent characteristics of its immobilized carrier, the immobilized filler is prone to swelling during the long-term operation of the system, resulting in increased pressure drop. Polyurethane (PU) sponge was used as the cross-linked skeleton of immobilized filler and compared with direct emulsified cross-linked immobilized filler for treating ethylbenzene gas. In the early stage, both fillers can maintain good performance despite changes in the inlet concentration and short-term stagnation. However, on the 107th day of operation, the immobilized filler experienced swelling, and the pressure drop sharply increased to 137.2 Pa, while the PU immobilized filler was still able to maintain a low-pressure drop level. The results of the microbial diversity analysis revealed that the microbial community structure of PU immobilized fillers remained relatively stable when responding to the fluctuations in operating conditions. PU sponges as the skeleton can effectively prolong the service life of the immobilized filler and improve the performance of the biotrickling filter.

Filtering on the Go: Effect of Filters on Gaze Pointing Accuracy During Physical Locomotion in Extended Reality.

Eye tracking filters have been shown to improve accuracy of gaze estimation and input for stationary settings. However, their effectiveness during physical movement remains underexplored. In this work, we compare common online filters in the context of physical locomotion in extended reality and propose alterations to improve them for on-the-go settings. We conducted a computational experiment where we simulate performance of the online filters using data on participants attending visual targets located in world-, path-, and two head-based reference frames while standing, walking, and jogging. Our results provide insights into the filters' effectiveness and factors that affect it, such as the amount of noise caused by locomotion and differences in compensatory eye movements, and demonstrate that filters with saccade detection prove most useful for on-the-go settings. We discuss the implications of our findings and conclude with guidance on gaze data filtering for interaction in extended reality.

A Review of the Challenges of Adaptive Filtering Technology in High-fidelity Audio Signal Processing

Abstract. High-fidelity audio signal processing plays an important role in modern audio technology. With the increasing demand for this technology in various audio application scenarios, the optimization of adaptive filters has emerged as a significant challenge in this field. This paper focuses on improving the performance of adaptive filters in high-fidelity audio signal processing which aims to improve the adaptability and efficiency of filters in complex audio environments by improving algorithms. In this study, the adaptive filtering algorithm based on wavelet transform and particle swarm optimization is used to verify the audio data processing by simulation and real data processing. The research data was collected using the standard audio signal database and the actual collected high-fidelity audio samples. The results show that the improved adaptive filter can significantly improve the performance of complex audio environments, improve the clarity and fidelity of audio signals and reduce the computational complexity. It is also suitable for real-time processing scenarios with limited resources. The conclusion shows that this method provides an efficient solution for high-fidelity audio signal processing and has a wide application prospect.

PET nano-woven luminescent fibers for efficient air filtration and fluorescence indication of particulate matter

Inhalable particulate matter poses significant health risks, and current air filtration materials often struggle with efficiently capturing particles smaller than 300 nm and providing real-time feedback on filtration performance. We present the synthesis and characterization of polyethylene terephthalate (PET) nano-woven luminescent fibers (PNWLFs), created through a positive and negative dual high-voltage electrospinning method. The PNWLFs feature a unique nano-woven structure composed of backbone fibers (200–1000 nm) and nanofibers (20–160 nm), which endow them with remarkable mechanical strength, maintaining a breaking force of 117.5 cN and structural integrity under a 138 mm water column. The fibers exhibit excellent breathability and waterproof performance, with a water vapor transmission rate of 4.69 kg/m2/day. More importantly, the PNWLFs demonstrate exceptional air filtration capabilities, achieving filtration efficiencies of 99.77 % for PM5.0, 99.76 % for PM2.5, 99.72 % for PM1.0, 99.53 % for PM0.5, and 99.40 % for PM0.3, with minimal pressure drop of 106 Pa. Additionally, these fibers possess a unique fluorescence-indicating function: the fluorescence intensity decreases in response to increasing particulate matter concentration and the number of filtration cycles, allowing for intuitive visual monitoring of filter performance and particulate levels. These attributes underscore the significant potential of PNWLFs synthesized by this work for advanced air filtration applications and effective air quality monitoring.

Filtration Performance of Biodegradable Electrospun Nanofibrous Membrane for Sub‐Micron Particles: A Systematic Review

AbstractNanofiber membranes receive considerable interest recently because of their distinctive structural features, facile preparation, as well as high filtering efficiency. Due to ever‐increasing air pollution, membranes made from biodegradable materials can play a crucial part in providing purified air with minimum concerns of environmental issues after the membrane's end of service life. The purpose of this systematic review is to assess the performance of biodegradable electrospun nanofibrous membrane filters toward air sub‐micron particles. To identify relevant studies, a systematic search is carried out in major scientific search engines including PubMed, Scopus, and the Web of Science. Data extraction is used to collect the necessary information on the membranes' structural properties, as well as filtration performance metrics such as efficiency, pressure drop, and quality factor. Among the electrospun membranes derived from biodegradable polymers, the polyvinyl alcohol (PVA)‐based electrospun membranes are more effective in filtration efficiency in capturing sub‐micron particles. The results highlight that these types of membranes are effective in filtration with low energy consumption, making them more apt for air purification. The use of such membranes can supply both high filtering performance and protection of the environment.

Second Order Extended Ensemble Filter for Non-linear Filtering

Whenever the state of a system must be estimated from noisy information, a state estimator is employed to fuse the data with the model to produce an accurate estimate of the state. When the system dynamics and observation models are linear, the Kalman Filter which is optimal, is used. However, in most applications of interest the system dynamics and observations equations are not- linear and suitable extensions of the Kalman Filter have been developed; for example, the Extended Kalman Filter(EKF). The Extended Kalman Filter is based on linearization by the Taylor series expansion about the mean of the state. This filtering process is however computationally expensive especially in high dimensional data. The cause for this is the high cost of integrating the equation of evolution of covariances. Due to this complexity in integration, new methods were sought known as the particle filters. It replaces linearization of non-linearities with Monte Carlo methods. The particle filter formed a basis for Ensemble Kalman Filter (EnKF) an extension of Kalman filter to non-linear filtering. The EnKF reduced the computational cost but its innovation process does not capture information sufficiently hence there is need to improve its performance. This study has developed a new filter, Second order Extended Ensemble Filter (SoEEF).We derived it from stochastic state models by expansion of expected values to the second order by use of Taylor series together with Monte Carlo method and Matlab. We used Lorenz 63 system of ordinary equations and differential Matlab to test the performance of the new filter. Then we compared its performance with four other filters like Bootstrap Particle Filter (BPF), First order Kalman Bucy Filter (FoEKBF),Second order Kalman Bucy Filter (SoKBF) and First order Extended Ensemble Filter (FoEEF). SoEEKF performs much better than the other four filters.

Robust global optimization of plasmonic filter based on Q factor analysis using graded index

Abstract To reduce the impact of uncertainties in various manufacturing processes while maintaining satisfactory performance level, we propose a robust global optimization approach for plasmonic filters based on extraordinary optical transmission by use of Q factor analysis with reasonable computational cost. The gradient index is employed as a metric for robustness, and the multiobjective genetic algorithm is selected as a global optimization tool. The figures of merit and gradient index are chosen as two objective functions with the design variables being the slit width, slit height, and period of the slit array, respectively. The finite element method is employed to investigate a variety of optical properties rigorously. The numerical optimization results demonstrate that the proposed approach provides improved effectiveness and efficiency in designing plasmonic filters under fabrication uncertainties by using Q factor analysis. The method proposed in this study enables systematic robust optimization while accounting for manufacturing uncertainties, which would be infeasible under typical time constraints. Specifically, within the proposed optimization framework, Q factor analysis can be employed due to a 20.60-times reduction in computational time. To the best of our knowledge, this represents the first robust optimization design for enhanced filter performance based on Q factor analysis in EOT, necessitating comprehensive spectrum calculations alongside fabrication tolerance considerations.

Impact of Directly Assimilating Radar Reflectivity Using a Reflectivity Operator Based on a Double-Moment Microphysics Scheme on the Analysis and Forecast of Typhoon Lekima (1909)

In previous studies, radar reflectivity is often directly assimilated using reflectivity operators based on a single-moment (SM) microphysics scheme, though the forecast model uses a double-moment (DM) microphysics scheme. With the fixed number concentrations, only the mixing ratios of hydrometeors are directly updated during the assimilation, which leads to a mismatch between the analyzed microphysical state variables and the microphysics scheme of the forecast model. In this study, the radar reflectivity is directly assimilated through an observation operator consistent with the DM Thompson microphysics scheme used in numerical integrations, and the impact of reflectivity operators based on SM and DM schemes on the analysis performance of the ensemble Kalman filter for typhoon Lekima on 9 August 2019 is evaluated. Reflectivity observations from a single operational weather radar in Wenzhou City, Zhejiang Province of China are assimilated. In addition, the dual-polarization observations from the same radar are used to evaluate the quality of the analysis. The analyzed reflectivity and dual-polarization characteristics obtained by different reflectivity operators are examined in detail. Compared with the experiments applying the reflectivity operator based on the SM Lin scheme, the use of a reflectivity operator consistent with the DM Thompson scheme adopted in the forecast model results in analyzed reflectivity and polarization characteristics that are more consistent with the observed characteristics in terms of general structure, location, and intensity. Forecasted reflectivity, 3 h accumulated precipitation, and typhoon intensity and track are also evaluated. The application of the reflectivity operator based on the DM scheme makes better forecasts of typhoon intensity, precipitation, and reflectivity, which also improves the forecast skills on typhoon tracks to a certain extent.

Evaluation of Effluent Quality Trends Before and After Filtration Through the Composite Filter from Shirere Wastewater Treatment Plant to River Isiukhu in Kakamega County, Kenya

The current stabilization ponds as wastewater treatment practices in urban areas have proven insufficient with continued discharge of untreated wastes into water bodies. Their challenge comes from inappropriate system selection and maintenance, improper design, construction mistakes, physical damage and hydraulic overload. Appropriate infrastructural technologies for waste removal that can be adopted in the drainage channels of effluents into water bodies are scarce. This study incorporates a reactor based composite filter of pumice and sand as an innovative approach for removing residual waste in effluents discharged from Shirere Wastewater Treatment Plant into River Isiukhu, Kakamega Municipality. The objective of the study was to evaluate the trend of effluent quality from Shirere wastewater treatment plant upto river Isiukhu before and after installation of composite granular filter. Effluents, drinking water from Shirere WWTP, Shikoye stream, River Isiukhu and protected spring along Shikoye stream, were collected using presterilized water sampling containers for microbial quality analysis at MMUST and KACWASCO laboratories. The measurements were carried out using UV-VIS spectrophotometer at 752 nanometer wavelengths. Research design was experimental. The average reduction of COD in the mid-season of June to August was 42.2 ±4.6%, being the highest. Concomitantly, the BOD removal by the filter in the season of June to August was19.6±7% and 15.6 ±3.5% for September to November. The average rate of TSS removal in June to August was 19.3±4.5% followed by 16.6±3.8% in September to November and 11.6±7% in March to May. The average rate of Nitrate removal in June to August was 41.8±7.6% followed by 30.0±2.2% for March to May and 25±8.6% for September to November. Phosphates had an average rate of removal in June to August at 31.9±2.7% followed by 20.6±4.8% for September to November and 20.0 ±4.3% for March to May. Specifically, for the first season of March – May 2021 at 200 mm filtration depth were carried out at effluent flow rate of 0.0032 and volume, 0.234 Concentrations of most parameters were above NEMA standards, like COD was 322mg/l yet maximum should be 100 mg/l. Therefore, it was concluded that silica pumice composite filter performance was achieved by big variations in the concentrations of COD, BOD, TSS, Phosphates and Nitrates at Shirere WWTP after filtration which was attributed to effective removing capacity. The effluent concentrations from sampling sites S1-S3 and S5-S7 were found to be above the NEEMA standards implying the high risk of using Isiukhu water and catchment area. Thus, this study recommended that, the composite filter reduced concentrations of all the parameters (COD, BOD, TSS, PO3, NO3) significantly from Shirere WWTP along Shikoye stream up to the confluence of river Isiukhu. Most of the parameters after filtration were ranging within the required standards of NEMA. The requisite measure of adopting new technology of composite filtration should be sustained.

Data-driven inverse mix design for sustainable alkali-activated materials

Alkali-activated materials (AAMs) are promising alternatives to ordinary Portland cement (OPC), but standardized mix design approaches are limited. This study introduces a machine learning-based framework for inverse mix design of AAMs, predicting optimal mixes based on target properties and sustainability. The model considers eight key factors, including precursor reactivity, activator properties, and liquid-to-binder ratio. It operates in four steps: (i) constructing forward prediction models, (ii) generating new mix designs, (iii) evaluating workability and strength, and (iv) filtering for performance and sustainability. Experiments validated the model, targeting fluidity >100% and compressive strengths of 40 MPa (A40) and 50 MPa (A50). The A40 and A50 mixes achieved fluidities of 147.7% and 170.0%, and 28-day compressive strengths of 41.5 and 57.5 MPa. Both had lower environmental impacts (GWP, AP, and EP) compared to OPC-based mortars. This framework enhances AAM design efficiency and sustainability for broader applications.

Liquid Crystal Enables Extraordinarily Precise Tunability for a High‐Q Ultra‐Narrowband Filter Based on a Quasi‐BIC Metasurface

AbstractNotch filters usually involve high costs, great difficulties in processing, and very limited tunability. By coating a nematic liquid crystal (LC) layer onto a well‐designed quasi‐bound states in the continuum (quasi‐BICs) metasurface, this work designs and demonstrates a high‐Q tunable filtering system with precise tunability in the near‐infrared spectral range. Optimal structural parameters and the filtering performance are first determined by numerical simulations and then confirmed in experiments. The precise tunability is enabled by modifying the LC molecules’ principal axes with an applied voltage, where the least distinguishable central wavelength interval is smaller than 0.3 nm, and the largest Q factor extracted from experiments can be ≈256.1. Compared to most of the commercial notch filters that work in the visible region and have no tunability, this work achieves an ultra‐narrowband filtering system that features low manufacture difficulty and cost, and great control of light propagation. The proposed design also opens new avenues for developing BIC‐based high‐Q devices with enhanced signal‐to‐noise ratio and multifunctional properties.

Assessing Adsorption and Desorption Performance in the Recovery of Volatile Organic Compounds

In this study, the activated carbon fiber filter design and VOC adsorption and desorption performance were evaluated based on the development of a filter regeneration device to treat VOCs in high efficiency and low cost. Activated carbon fiber (ACF) has the advantage of fast adsorption speed and high adsorption capacity because micropores are formed on the surface and a large specific surface area. However, the specific gravity is about 25 times lower than that of activated carbon (AC), so the amount of adsorbent that can fill the same volume is small. In order to solve this problem, the regeneration device is implemented by repeating adsorption and regeneration for a short time, and a cylindrical adsorption filter made of activated carbon fiber is designed according to the operating conditions of the regeneration device. At this time, the pollutant gas and regenerated air are uniformly distributed over the entire adsorbent, and the flow characteristics according to the supply of the pollutant gas and the regeneration gas are analyzed. When the size of the lower part of the cylindrical adsorption filter is smaller than the size of the upper part under the condition that the pollutant gas flows downward, a uniform distribution of the pollutant gas is possible. In addition, as the space velocity decreases, the adsorption capacity decreases, and the differential pressure increases rapidly. Through the regeneration experiment, it was confirmed that the desorption concentration of MEK was higher and the desorption concentration was higher. In addition, the regenerated air is uniformly dispersed throughout the adsorption filter, toluene, o-xylene, and methyl ethyl ketone, which are representative substances of volatile organic compounds (VOCs), are injected with 400 ppm, and then regenerated air is supplied at 150 °C to analyze adsorption characteristics and regeneration concentrations. As a result of the experiment, the adsorption capacity ratio to 1 g of regeneration air according to the type of VOCs was 0.48, 0.36, and 0.25 g in the order of o-xylene, toluene, and methyl ethyl ketone. In addition, as the space velocity decreases, the adsorption capacity decreases, and the differential pressure increases rapidly. Through the regeneration experiment, it was confirmed that the desorption concentration of MEK was higher and the desorption concentration of o-xylene was discharged at a relatively low concentration. Moreover, even if the adsorption concentration changes, there was no difference in the regeneration concentration change. Therefore, the filter was designed based on the spatial speed of the regeneration device of 51,000 -h or less, and the adsorption capacity ratio to 1 g of the regeneration air amount was 0.1 g, thereby enhancing the filter's recycling performance and VOCs emission effect.

Study on the Robust Filter Method of SINS/DVL Integrated Navigation Systems in a Complex Underwater Environment

This paper proposes an improved adaptive filtering algorithm based on the Sage–Husa adaptive Kalman filtering algorithm to address the issue of measurement noise characteristics impacting the navigation accuracy in strapdown inertial navigation system (SINS)/Doppler Velocity Log (DVL) integrated navigation systems. Addressing the non-positive definite matrix problem prevalent in traditional adaptive filtering algorithms and aiming to enhance measurement noise estimation accuracy, this method incorporates upper and lower thresholds determined by a discrimination factor. In the presence of abnormal measurement data, these thresholds are utilized to adjust the covariance of the innovation, subsequently re-estimating the system’s measurement noise through a decision factor based on the innovation. Simulation and experiment results demonstrate that the proposed improved adaptive filtering algorithm outperforms the classical Kalman filter (KF) in terms of navigation accuracy and stability. Furthermore, the filtering performance surpasses that of the Sage–Husa algorithm. The simulation results in this paper show that the relative position positioning error of the improved method is reduced by 49.44% compared with the Sage–Husa filtering method.

Performance of intermittent sand and coke filters for the removal of size-ranged microplastics

Microplastics (MPs) are a growing environmental problem that threaten living organisms, especially in water ecosystems. One of the main sources of MPs in water environments are wastewater treatment plants, which remove the majority of these micropollutants, but large amounts keep reaching the environment daily. To achieve a larger removal on MPs in wastewater, intermittent filtration sets as an efficient and cheap alternative. In this work, three laboratory-scale filters were tested, with different filtration media (sand, sand/coke and coke) to compare their performance with PP-spiked freshwater and real wastewater samples in removing MPs from different size ranges, from larger than 32 µm to 100 µm. Sand/coke and coke filters showed the best results, with a general microplastic removal efficiency of up to 92.79 ± 2.78 % for wastewater and 89.56 ± 2.19 % for PP-spiked water. This removal efficiency decreased with smaller MPs, reaching up to 90.87 ± 3.46 % for wastewater and 76.28 ± 8.54 % for PP-spiked water. Significant differences were found on efficiencies for PP-spiked water and wastewater, especially in the range from 32 to 63 µm, where biofilm formed on pores surface with wastewater filtration may play an important role for the removal of these MPs.

Novel design and implementation of 3d packaged wideband bandpass filters

This study presents an innovative method for designing a 3D packaged wideband bandpass filter (BPF) by vertically integrating a high-pass filter (HPF) and a low-pass filter (LPF) using an air cavity and vertical interconnect accesses (VIAs). This integration enhances performance while significantly reducing system size. The fabricated BPF, constructed on multilayer substrates, achieves a passband from 2.175 to 4.2 GHz with less than 2.5 dB insertion loss and a return loss exceeding 10 dB. The design utilizes a partial substrate integrated suspended line (SISL) structure, enabling precise control over the equivalent dielectric constant and characteristic impedance to optimize insertion loss. The height of the air cavity, determined through theoretical analysis and S-parameter inversion, is critical for achieving optimal filter performance. The methodology allows for independent circuit designs on each layer, resulting in a 3D assembly. This refined approach makes it easier to produce compact bandpass and multi-band filters, simplifying circuit development and enabling scalable fabrication. This design is versatile across different frequency ranges, demonstrating significant practical and theoretical benefits.

Streamlining process development and scale-up: Risk assessment to reduce workload in primary protein recovery

Risk assessment is an integral aspect of the Quality-by-Design strategy to identify potential obstacles at every stage of biopharmaceutical production, from process development to tech transfer. We explored flow process chart, root cause analysis, and failure mode and effects analysis, to assess the scale-up of bacterial cell disruption and its influence on centrifugation and filtration steps. The Ishikawa diagram suggests that data on the impact of homogenizer valve design on product release, impurity profile, particle size distribution, viscosity, and dsDNA fragment size are missing which were collected experimentally for this study. Cell lysates from micro-, lab- and pilot scales cell disruption were analyzed for the above-mentioned parameters. Process parameters affecting these output parameters were identified on each individual scale. Cell disruption on the micro scale was performed in a bead mill. High pressure homogenization was used on lab- and pilot scales. Cell disintegration by bead milling delivers homogenates of product and impurity content comparable to those on bench scale but with 3-fold higher viscosity and significantly larger dsDNA fragments, 8.0 instead of 1.0 kbp, respectively. Miniaturized pressure flow curves identified dsDNA fragment sizes as critical for filter performance during clarification. Combining risk assessment, micro scale cell disintegration and bench scale pressure flow curves allows for selective and efficient process development, and scale up for primary recovery steps.