Minimum Energy Input Research Articles

Comparing Exergy Analysis and Physical Optimum Method Regarding an Induction Furnace

In order to achieve energy and climate goals, energy and resource efficiency are considered a key measure. Limit-value-oriented methods such as the exergy analysis and the physical optimum method are used to show the limits of efficiency improvement. In this context, the physical optimum represents the theoretical ideal reference process. Despite their similarities, no comprehensive comparison to the exergy analysis has been carried out yet. Thus, the purpose of this study is to close this gap by examining differences and intersections using the example of an induction furnace. The minimum energy input according to the physical optimum method is 1327 MJ/t whereas the exergy of the melting product is 1393 MJ/t, depending on transit flows taken into account. The exergy analysis extends considerably beyond the physical optimum method in terms of the complexity and accuracy of the assessment of material flows by using exergy units. The exergy analysis makes clear which exergy is linked to the losses and thus reveals the potential for coupling processes. This results in different areas of application for the two methods.

Energy-saving trajectory planning by using Fourier sine series and tracking control for a mechatronic elevator system

In this paper, Lagrangian method is proposed to formulate dynamic model for a mechatronic elevator system, which includes mechanical and electrical parts. Lagrange equations, i.e. the torque balance equation and voltage balance equation, are derived from the kinetic energy, potential energy and virtual work of the mechatronic system. From the dynamic equations, the energy balance equation is obtained including electromagnetic energy, electrical dissipation energy, mechanical kinetic energy, mechanical dissipation energy, and the mechanical potential energy. The minimum-energy trajectory by using Fourier sine series (FSS) and power series are found by real-coded genetic algorithm. From simulation results, it is found that FSS with less order can find the minimum input energy more quickly than the power series. The four-degree (4-D) FSS trajectory is given as a reference one for the adaptive tracking control. It is found that the proposed adaptive controller has good tracking performance for the 4-D FSS angular displacement and velocity.

Stability-analysis-based optimization to control flow separation over a diffusing passage

We present a stability-analysis-based optimization approach that minimizes the growth rate of the least stable mode associated with the flow structure governing flow separation. We compare this approach with a classic optimization approach that minimizes an integral function related to pressure loss. We analyze both approaches on a two-dimensional model that mimics the diffusing passage present in the aft portion of the suction side of a low-pressure turbine. This zone is prone to boundary layer detachment at low Reynolds numbers, while fully attached flow is present at higher Reynolds numbers. The goal of the optimization is to design a local blowing technique to prevent boundary layer detachment at low Reynolds numbers and thereby reducing the dynamic head pressure loss with a minimum energy input. We simulate the problem using the compressible Reynolds-averaged Navier–Stokes equations (with the k–ω turbulence model) and perform a stability analysis on the mean flow. We then use the stability information and associated sensitivity (through adjoints) to provide insights into local blowing and thereby guide the optimization. The two optimization strategies use the blowing location, blowing rate, and blowing angle as the optimization variables. The first strategy minimizes a classic global integral function, including input and output pressure losses. The second approach minimizes the amplification rate of the least stable eigenvalue resulting from a stability analysis. The targeted mode governs the detached recirculation, and stabilizing its amplification rate leads to attached flow and minimum losses. Indeed, both strategies lead to attached flows and similar optimal values for the blowing location and to enhanced performance. It is concluded that the stability-analysis-based optimization provides results comparable to those from a classic optimization approach and can be useful for cases where there is no clear integral functional to guide the optimization procedure (e.g., pressure loss).

Multi-Element Containing Precious Group Metal-Free Electrocatalysts for Efficient Hydrogen Evolution Reaction in PEM Water Electrolysis

Electricity driven proton exchange membrane-based water electrolysis (PEMWE) has demonstrated considerable credibility in recent years, establishing high competency enabling PEMWE technology for rapid generation of clean hydrogen fuel 1-7. In order to attain the high efficiency needed and successful commercialization of PEMWE, there is a critical need to identify highly active, robust, and earth-abundant electrocatalysts for accelerating the hydrogen evolution reaction (HER) with minimum energy input 8. In the pursuit of achieving this goal, in the present work, employing the density functional theory (DFT) based calculations for rationalizing the thermodynamics and reaction kinetics of HER, we have investigated the platinum group metal (PGM)-free, earth-abundant, transition metal non-oxide (TMN) based electrocatalysts for acid mediated HER in PEMWE. Based on the theoretical calculations, the as-synthesized TMN electrocatalyst compositions reveal optimized hydrogen adsorption free energies (ΔGH *) and beneficial electronic structures modification, offering superior charge transfer kinetics, lower reaction barrier, low water contact angle (7o) suggesting high wettability (Fig. 1), and high electrocatalytic activity for HER. Furthermore, the highly active electrocatalyst compositions display excellent long term electrochemical HER stability in acidic media, with no significant obvious degradation in current density. The as-synthesized electrocatalysts thus, has propensity for exhibiting robust HER performance with excellent structural and mechanical integrity. The experimental results are in excellent agreement with the DFT calculations which further accentuate the incorporation of suitable PGM-free dopants into the TMN compositions resulting in optimized electronic structures lowering the HER reaction barriers. The system therefore offers improved electrocatalytic performance for HER which is comparable to state-of-the-art Pt/C electrocatalysts. Accordingly, the as-synthesized PGM-free electrocatalysts can be considered as reliable HER candidates, vital for the development of acid mediated PEM based water splitting employing PGM-free electrocatalysts. Results of this study will be presented and discussed. Acknowledgements: Financial support of NSF-CBET grant# 1511390, Edward R. Weidlein Chair Professorship funds and the Center for Complex Engineered Multifunctional Materials (CCEMM) is acknowledged.

Solid Acid Electrochemical Cell for the Production of Hydrogen from Ammonia

Summary Production of high-purity hydrogen by thermal-electrochemical decomposition of ammonia at an intermediate temperature of 250°C is demonstrated. The process is enabled by use of a solid-acid-based electrochemical cell (SAEC) in combination with a bilayered anode, comprising a thermal-cracking catalyst layer and a hydrogen electrooxidation catalyst layer. Cs-promoted Ru on carbon nanotubes (Ru/CNT) serves as the thermal decomposition catalyst, and Pt on carbon black mixed with CsH2PO4 is used to catalyze hydrogen electrooxidation. Cells were operated at 250°C with humidified dilute ammonia supplied to the anode and humidified hydrogen supplied to the counter electrode. A current density of 435 mA/cm2 was achieved at a potential of 0.4 V and ammonia flow rate of 30 sccm. With a demonstrated faradic efficiency for hydrogen production of 100%, the process yields hydrogen at a rate of 1.48 m o l H 2 / g c a t h .

High Cycle Fatigue Performance of LPBF 304L Stainless Steel at Nominal and Optimized Parameters.

In additive manufacturing, the variation of the fabrication process parameters influences the mechanical properties of a material such as tensile strength, impact toughness, hardness, fatigue strength, and so forth, but fatigue testing of metals fabricated with all different sets of process parameters is a very expensive and time-consuming process. Therefore, the nominal process parameters by means of minimum energy input were first identified for a dense part and then the optimized process parameters were determined based on the tensile and impact toughness test results obtained for 304L stainless steel deposited in laser powder bed fusion (LPBF) process. Later, the high cycle fatigue performance was investigated for the material built with these two sets of parameters at horizontal, vertical, and inclined orientation. In this paper, displacement controlled fully reversed (R = −1) bending type fatigue tests at different levels of displacement amplitude were performed on Krouse type miniature specimens. The test results were compared and analyzed by applying the control signal monitoring (CSM) method. The analysis shows that specimen built-in horizontal direction for optimized parameters demonstrates the highest fatigue strength while the vertical specimen built with nominal parameters exhibits the lowest strength.

Formic acid and methanol electro-oxidation and counter hydrogen production using nano high entropy catalyst

Renewable harvesting of clean energy using the benefits of multi-metallic catalytic materials of high entropy alloy (HEA, equimolar Cu–Ag–Au–Pt–Pd) from formic acid with minimum energy input has been achieved in the present investigation. The synergistic effect of pristine elements in the multi-metallic HEA drives the electro-oxidation reaction towards non-carbonaceous pathway. The atomistic based simulations based on DFT rationalize the distinct lowering of the d-band center for the individual atoms in the HEA as compared to the pristine counterparts. Further this catalytic activity of the HEA has also been extended to methanol electro-oxidation to show the unique capability of the novel catalyst. The nanostructured HEA, prepared using a combination of casting and cryomilling techniques can further be utilized as the fuel cell anode in the direct formic acid/methanol fuel cells (DFFE).

Influence of luminous flux parameters on the formation of re-weeding of hemp crops

Light (energy) growing conditions of hemp plants have a direct effect on both crop plants and their habitat, as well as on new seedling plants of weeds that began their vegetation after soil herbicides weakened their protective function. The appearance of such weeds in crops is called re-weeding. Re-weeding is difficult to control. 
 It is fair to say that the density of hemp crops and, consequently, their optical density is a very effective, cheap and environmentally friendly factor influencing weeding processes. The application of such factors of influence on the indicators of re-weeding of crops is especially effective, when the application of any agronomic or chemical methods on new weed seedlings is very difficult or simply impossible.
 Studies conducted during 2014‒2016 in the field experiment of the Institute of Bast Crops of NAAS to determine the influence of light regimes of hemp sowing on the formation of re-weeding crops provided five options with different stocking densities of hemp sowing, which formed different indicators of optical density of crops. The experiment determined such indicators of the light regime as the incident energy flux of the headlights and the transmission of light by sowing to the ground. Weed surveys were performed according to the requirements of the "Pesticide Test and Application Methods". Crop weeds were determined quantitatively and quantitatively by weight.
 As a result of the conducted researches the regularities of weed formation at different density of stems, as well as between weed parameters and light regimes of sowing hemp crops were established. There is a direct linear relationship between the transmission of light to the soil by sowing hemp and the number and weight of weeds. The critical dates for the release of FAR energy into the soil for re-weeding were the third decade of July and the third decade of September. With a standing plant density of 1.65 million units/ha, conditions developed under which most weed plants in repeated weeding could not reach the virgin stage of organogenesis. That is, it can be argued that it is in crops with a stem density of 1.65 million units/ha conditions are achieved for the least development of re-weeding due to the minimum energy input of the headlights required for full generative productivity of weeds.
 Thus, the development of methods for controlling the processes of re-weeding of hemp crops based on phytocenotic factors deserve widespread introduction into agricultural production, as quite effective and environmentally friendly.

An Innovative Control Allocation Framework for a Novel Tiltrotor Aircraft

Control allocation is still a challenge for tiltrotor aircraft due to effectors’ redundancy, dramatic nonlinearities and cross-coupling. Besides this, the external disturbance caused by the unique configuration of tiltrotor such as larger wing area and tiltable mechanism puts forward extra security requirement on control allocation method. Thus, this paper proposes an innovative control allocation framework from the perspective of flight safety to address this problem. Firstly, an effector distribution management scheme based on remaining control ability index (RCAI) is developed to reduce the effector saturation and ensure flight safety. Secondly, the energy consumption models for two classes of effectors: thrust vectoring and aerodynamic surfaces are introduced respectively for the subsequent optimization problem mathematically. Then, the null space transition is used to find the minimum-energy control input of effectors. Finally, key parameters of energy consumption model are identified by experiments. The real-time hardware-in-loop simulation platform is adopted to demonstrate the effectiveness of the proposed control allocation framework. Experimental results show that the energy consumption of proposed method can reduce by about 63.5% comparing to traditional control allocation method.

Stochastic input design problems for the frequency response in Bayesian identification

Recently, the research of identification input design for Bayesian methods has been actively investigated. Either the problem is formulated as a non-convex problem with difficulty in solving or relaxed as a convex problem with a price of some conservativeness. In this contribution, a new minimum power input design problem is formulated by viewing the input as a stochastic process. We seek the minimum energy input with variance constraints over a frequency band. By exploiting the generalized Kalman-Yakubovich-Popov lemma, the stochastic consideration facilitates the input design problem to be presented as a convex problem whose decision variables are a finite number of autocorrelation coefficients. We obtain the autocorrelation coefficients of the desired stochastic input signal by solving the convex problem and extend them by the maximum entropy extension. Then, a specific identification input is sampled from the obtained stochastic process. Simulations results demonstrate the effectiveness of the proposed method.

Evaluating the effectiveness of HOCl application on odor reduction and earthworm population growth during vermicomposting of food waste employing Eisenia fetida

Vermicomposting has been recommended as an eco-friendly method to transform organic waste into nutrient resources with minimum energy input. However, odor and pest issues associated with this method limit the use of vermicomposting, especially in indoor conditions. This study evaluated the effectiveness of applying hypochlorous acid (HOCl) to deodorize the vermicomposting process and improve the breeding environment for earthworms (Eisenia fetida). The deodorization performance of HOCl was compared by measuring the amount of ammonia (NH3) and amine (R-NH2) released from the decaying process of two types of food waste: HOCl-treated (HTW) waste and non-treated waste (NTW). The total and individual weights of earthworms in the waste treated with HOCl was measured to evaluate the impact on earthworm reproduction after applying HOCl. The results showed that HOCl application could reduce NH3 by 40% and R-NH2 by 80%, and increase the earthworm population size and total weight by up to 29% and 92%, respectively, compared to the control group. These results suggest that HOCl application is potentially an efficient method to control the odor and to boost earthworm reproduction and thus facilitate vermicomposting for improved food waste treatment and environmental quality.

Simulation and Optimization of a Multitubular Reactor Train for Acrylic Acid Production

Acrylic acid is a major chemical intermediate used in the production of acrylate esters. The most popular route for the manufacture of ester grade acrylic acid is via propylene oxidation. In a typical process, chemical grade propylene is contacted with steam and air in a catalytic reactor train to produce the target compound with carbon dioxide and acetic acid as the major byproducts. Various catalytic systems exist, offering both high selectivity and conversion, and operation can be based on different reactor types and configurations. The highly exothermic nature of the reactions necessitates efficient removal of the reaction heat. In this work the rigorous simulation and optimization of a two-step multitubular oxidation reactor system for the production of acrylic acid was undertaken on the ASPEN Plus platform, with particular emphasis on minimizing energy requirements. In developing the model, several critical parameters were identified for proper representation of the reaction system in the sequential simulation platform. These included adjustments to the properties of molten salt thermal fluids for accurate determination of flow characteristics on the shell side, comprehensive and interactively coupled calculation of the overall heat transfer coefficient and the use of inert pre-heating and oxidation pre-heating zones at the front end on the propylene oxidation reactor tubes. The resultant model was successfully used to optimize for acrylic acid production with minimum energy input, demonstrating the applicability of digital twins for process analysis.

Effect of single spark micro-EDM on crater size of different alloys

Owing to the fact of continuous discharges in RC circuit based μ-EDM process, it is indeed very difficult to analyse difficult-to-control single discharge pulse. This work is thus aimed to develop an innovative technique for generating single discharge in the process. An electrical circuit, parallel to the existing discharge circuit of μ-EDM, has been integrated in-house for the purpose and verified for its applicability over a wide range of metal alloys. For example, single crater diameters of approximately 7μm, 10μm and 18μm have been achieved for stainless steel, Inconel and brass respectively at minimum energy input. The single discharge generatorhas been developed expecting it would be helpful in gathering information such as volume removal by each discharge which will definitely lead to development of a robust thermal model for material removal in μ-EDM.

Effects of additives on the particle morphology and aqueous dispersibility of foam-spray dried cellulose nanocrystal suspensions

Cellulose nanocrystals (CNCs) are inherently hydrophilic; even so, their dispersions in water based applications such as rheology modifiers, coatings, and emulsion systems do not often produce perfect dispersions with a minimum energy input. Supplying the CNCs in dry granular powder form is needed in the industrial scale of production because of its easier handling, storage and transportation characteristics. Spray drying is the preferred industrial method for drying acid hydrolyzed CNC suspensions. However, spray drying often causes poor dispersion of dried CNC granules into individual nanoparticles in aqueous solutions if not mixed with high energy input. This study investigates foam-spray drying of CNC particles to enhance their dispersibility in water. Non-ionic 10-mole ethoxylated octylphenol surfactant (OPE-100) and methyl cellulose polymer (MC) were used as additives to assist the foaming of CNC suspensions. Foam-spray drying experiments were carried out under constant process conditions such as inlet and outlet temperatures, gas and liquid flow rates and concentrations of CNCs. We focus on the effects of 10-mole ethoxylated octylphenol surfactant (OPE-100) and methyl cellulose polymer (MC) as additives and foaming of CNCs suspension on the morphology of dried CNC aggregates and their dispersion in water. Our work also describes the molecular interaction mechanisms of CNCs with methyl cellulose and OPE-100 by means of isothermal titration calorimetry and surface charge of the coated CNCs. The addition of nonionic surfactant OPE-100 along with methyl cellulose polymer resulted in spray drying of CNC aggregates with the best water dispersion characteristics. While methyl cellulose generated foams, OPE-100 lowered the inverse thermal gelling of methyl cellulose in spray drying.

Thermodynamic analysis of a novel wood drying system based on self-heat recuperation technology

ABSTRACT The issue of energy consumption in the field of wood drying has attracted widespread concern worldwide. In this paper, combining with the self-heat recuperation technology, a novel self-heat recuperation wood drying system (SHRWDS) with a fixed bed dryer is proposed to recover the sensible heat and latent heat of humid air, which is not fully utilized in the general drying process of wood. Mathematical models of the SHRWDS based on the conservation of mass and energy are established, and the effects of drying temperature, airspeed, and compression ratio on the energy and exergy input as well as the economy of the whole system are also carried out. The simulation results show that the drying temperature and the airspeed have a positive influence on the system performance, with optimal values, while the effect of the compression ratio is closely related to the relative humidity of the humid air at the outlet of the dryer. Furthermore, the minimum energy input of 77.23 kJ/s and exergy input of 28.27 kJ/s for the system are obtained at the condition of t= 60°C, v= 1.5 m/s, and φ= 90%, while the minimum annual consumption of standard coal volume and the lowest cost of wood drying for the SHRWDS are 68.34 t and 16.54 $/t. All of this indicates the remarkable superiority of the presented system compared with the traditional device.

Hamiltonian-based minimum-energy trajectory planning and tracking control for a motor-table system: part II system identification and adaptive tracking control

In this paper, the motor-table system is realized to plan the minimum input energy trajectory (MIET) based on Hamiltonian by minimum input energy control (MIEC) approach. In the motor-table system, the unknown parameters are identified by particle swarm optimization. We can identify the parameters experimentally and the MIEC methods are implemented to find the MIET. The adaptive tracking controller is proposed to track the MIET to overcome the nonlinear friction force and external disturbance. Moreover, trapezoidal trajectory and regulator control are compared with the MIET by the proposed adaptive tracking controller. Finally, the MIET based on the adaptive tracking controller can obtain the minimum energy control input and robustness performance for the motor-table system. The numerical simulations and experimental results are demonstrated the proposed strategy successfully.

Hamiltonian-based minimum-energy trajectory planning and tracking control for a motor-table system: part I minimum-energy methods in trajectory planning

In this paper, we propose the minimum energy control input based on Hamiltonian strategy for the motor-table system. The energy equation of the motor-table system contains of the input energy, dissipation energy, potential energy and output energy, and includes electrical and mechanical energies. The methods of the minimum control effort (MCE), minimum input energy control (MIEC), minimum dissipation energy control (MDEC) and trapezoidal trajectory energy control are compared for the motor-table system. From the numerical results, we can find that the MIEC and MDEC approaches can obtain the same minimum input energy. Traditionally, the MCE approach was regarded as the minimum energy control in the previous study. However, we have demonstrated that the MCE approach is not the minimum energy control in this paper.

Distributed Norm Optimal Iterative Learning Control for Point-to-Point Consensus Tracking

High performance consensus tracking of networked dynamical systems working repetitively is an important class of coordination problems and it has found many applications in different areas. Recently, iterative learning control (ILC), which does not require a highly accurate model to achieve the high performance requirement, has been developed for the consensus tracking problem. Most of existing ILC algorithms consider about the tracking of a reference defined over the whole trial length, while the Point-to-Point (P2P) task where the emphasis is placed on the tracking of intermediate time instant points, has not been explored. To bridge this gap, we develop a norm optimal ILC (NOILC) algorithm for P2P consensus tracking problem that guarantees not only the monotonic convergence of consensus tracking error norm to zero, but also the convergence of input to the minimum input energy solution, which is desired in practice. Moreover, using the idea of the alternating direction method of multipliers, we develop a distributed implementation method for the proposed algorithm, allowing the resulting algorithm to be applied to large scale networked dynamical systems. Rigorous analysis of the algorithm’s properties is provided and numerical simulations are given to verify its effectiveness.

Optimal phase control of biological oscillators using augmented phase reduction

We develop a novel optimal control algorithm to change the phase of an oscillator using a minimum energy input, which also minimizes the oscillator's transversal distance to the uncontrolled periodic orbit. Our algorithm uses a two-dimensional reduction technique based on both isochrons and isostables. We develop a novel method to eliminate cardiac alternans by connecting our control algorithm with the underlying physiological problem. We also describe how the devised algorithm can be used for spike timing control which can potentially help with motor symptoms of essential and parkinsonian tremor, and aid in treating jet lag. To demonstrate the advantages of this algorithm, we compare it with a previously proposed optimal control algorithm based on standard phase reduction for the Hopf bifurcation normal form, and models for cardiac pacemaker cells, thalamic neurons, and circadian gene regulation cycle in the suprachiasmatic nucleus. We show that our control algorithm is effective even when a large phase change is required or when the nontrivial Floquet multiplier is close to unity; in such cases, the previously proposed control algorithm fails.

Eco-friendly and low-cost Enhanced Pond and Wetland (EPW) system for the treatment of secondary wastewater effluent

To demonstrate the feasibility of Enhanced Pond and Wetland (EPW) system for the treatment of Biological Trickling Filter (BTF) effluent, pilot-scale EPW systems were installed and operated in New Zealand climate conditions. The system consisted of: two High Rate Algal Ponds (HRAPs) followed by gravity Algal Harvesters (AHs), two Surface Flow Constructed Wetlands (SFCWs), and a Woodchip Denitrification Filter (WDF). The wastewater treatment performance of each treatment component was monitored fortnightly over six months (late autumn to winter) in terms of TSS, total and soluble BOD5, nutrients (N and P) and E.coli removal. Algal biomass production, algal harvest efficiency, and algal dominance in the HRAPs were also determined. The pilot-scale system maintained low final effluent TSS and BOD5 concentrations below 5 and 8 mg L−1 respectively, and achieved high removal of nitrogen (NH4-N: ∼95%; NO3-N: 77%), phosphorus (DRP: ∼65%) and E. coli (at least 3-log E. coli removal) throughout the experimental period. Particularly in autumn, the HRAPs achieved almost complete removal of both NH4-N (5.0 to <0.3 mg L−1) and NO3-N (3.4 to <0.2 mg L−1) mainly through algal assimilation. Furthermore, when sunlight U.V radiation was high, ∼4-log E. coli removal (104 to <2 cfu/100 ml) was achieved in the HRAPs mainly through sunlight disinfection. The HRAPs had algal biomass productivity of 7.2 and 4.1 g m−2 d−1 in autumn and winter respectively, and the algal biomass was efficiently removed in AHs by gravity sedimentation (∼80% TSS removal after 6.5 h settling) through bio-flocculation under nitrogen limiting conditions (<0.5 mg L−1). Overall, the Enhanced Pond and Wetland system can efficiently treat secondary wastewater effluent from a domestic wastewater treatment plant and produce a high quality final effluent with minimum energy inputs.