Maximum Power Principle Research Articles

Planetary Energy Flow and Entropy Production Rate by Earth from 2002 to 2023.

In this work, satellite data from the Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are analyzed to determine how the global absorbed sunlight and global entropy production rates have changed from 2002 to 2023. The data is used to test hypotheses derived from the Maximum Power Principle (MPP) and Maximum Entropy Production Principle (MEP) about the evolution of Earth's surface and atmosphere. The results indicate that both the rate of absorbed sunlight and global entropy production have increased over the last 20 years, which is consistent with the predictions of both hypotheses. Given the acceptance of the MPP or MEP, some peripheral extensions and nuances are discussed.

Relativistic Motion in the Uniform Field: The Alignment Effect

We describe the essence of the so-called “alignment effect” from the standpoint of the maximum power principle and consider the main features of this effect within the framework of the relativistic approach. The paper is addressed to undergraduates studying the basics of the special theory of relativity.

Maximum power in evolution, ecology and economics.

Ludwig Boltzmann suggested that natural selection was fundamentally a struggle among organisms for available energy. Alfred Lotka argued that organisms that capture and use more energy than their competition will have a selective advantage in the evolutionary process, i.e. the Darwinian notion of evolution was based on a fundamental, generalized energy principle. He extended this general principle from the energetics of a single organism or species to the energetics of entire energy pathways through ecosystems. Howard Odum and Richard Pinkerton, building on Lotka, extended this concept to 'The maximum power principle' and applied it to many biological and physical systems including human economies. We examine this history and how these ideas relate to concepts from other disciplines including philosophy. But there has been considerable confusion in understanding and applying these concepts which we attempt to resolve while providing various examples from routine life and discussing some unresolved issues. This article is part of the theme issue 'Thermodynamics 2.0: Bridging the natural and social sciences (Part 2)'.

Analytical framework based on thermodynamics to estimate spatially distributed surface energy fluxes from remotely sensed radiations

The Limited surface observations of turbulent heat fluxes result in incomplete knowledge about the surface energy balance that drives the climate system. The highly parameterized surface energy balance models suffer from significant uncertainties. Remote sensing information of incoming and outgoing radiation fluxes are important input variables for turbulent heat flux models, though analytical solutions of surface energy budget from these variables are yet to be derived. Here, we developed a novel, purely physics-based analytical method grounded on the thermodynamic principle of maximum power. The approach derives the total turbulent heat flux only from the four inputs of incoming and outgoing longwave and shortwave radiations at the land surface, which are available from remotely sensed satellite data. The proposed approach does not use any parameterization, unlike the existing surface energy balance models, and hence does not suffer from uncertainty due to the same. We validated our methodology with 102 eddy covariance observation stations around the globe with different land use land covers from FLUXNET2015 and available urban datasets. Based on monthly averages of the total turbulent flux estimates for the eddy covariance sites, we observed root-mean-square error (RMSE) of 23.2 ± 10.9 Wm−2, a mean bias error (MBE) of 11.9 ± 13.1 Wm−2 and R2 value of 0.86 ± 0.15. Using the satellite observations of radiation fluxes from CERES at a spatial resolution of 10, we obtained the global flux field of total turbulent flux (QJ) and land surface heat storage (ΔQs) fluxes. On validation of QJ with FLUXNET sites for six grids for different land use land cover, we found RMSE of 20.1 ± 7 Wm−2, MBE of 14.4 ± 9 Wm−2 and R2 value of 0.96 ± 0.02. Further, from the evaporative stress factor of GLEAM, which is based on microwave remotely sensed vegetation optical depth and root zone soil moisture, we have obtained spatially distributed global estimates of Sensible(H) and latent heat (LE). In addition, our analytical estimates address the distribution of residual energy associated with the surface energy balance closure problem driven by the land use land cover. The theoretical estimates of all surface energy balance components from remote sensing based observations will improve our understanding of surface warming for different land use land covers across the globe.

From maximum force to the field equations of general relativity and implications

There are at least two ways to deduce Einstein’s field equations from the principle of maximum force [Formula: see text] or from the equivalent principle of maximum power [Formula: see text]. Tests in gravitational wave astronomy, cosmology, and numerical gravitation confirm the two principles. Apparent paradoxes about the limits can all be resolved. Several related bounds arise. The limits illuminate the beauty, consistency and simplicity of general relativity from an unusual perspective.

Comment on “Maximum force and cosmic censorship”

Despite suggestions to the contrary, no counterargument to the principle of maximum force or to the equivalent principle of maximum power has yet been provided.

Thermodynamics of urban growth revealed by city scaling

Cities are complex systems, where micro-scale phenomena lead to emergent, macro-scale patterns. Scaling in cities – the study of how characteristics of cities change with urban population – has been explained based on social interactions and networks, but cities are also governed by the laws of physics, such as thermodynamics and conservation of mass. Here we explore scaling laws in the context of the city as a far-from-equilibrium thermodynamic system, showing how scaling phenomena are consistent with ideas of cities as dissipative systems, the emergence of higher-order structures, and the Maximum Power Principle. We theorize that as cities grow, they use an increasing amount of energy and resources to produce an incremental change in useful work done. Furthermore, they require additional energy and materials to build higher-order structures, such as transportation systems, to overcome increasing density and congestion. We support our theoretical approach with new empirically observed scaling relationships.

Environmental control on the distribution of metabolic strategies of benthic microbial mats in Lake Fryxell, Antarctica.

Ecological theories posit that heterogeneity in environmental conditions greatly affects community structure and function. However, the degree to which ecological theory developed using plant- and animal-dominated systems applies to microbiomes is unclear. Investigating the metabolic strategies found in microbiomes are particularly informative for testing the universality of ecological theories because microorganisms have far wider metabolic capacity than plants and animals. We used metagenomic analyses to explore the relationships between the energy and physicochemical gradients in Lake Fryxell and the metabolic capacity of its benthic microbiome. Statistical analysis of the relative abundance of metabolic marker genes and gene family diversity shows that oxygenic photosynthesis, carbon fixation, and flavin-based electron bifurcation differentiate mats growing in different environmental conditions. The pattern of gene family diversity points to the likely importance of temporal environmental heterogeneity in addition to resource gradients. Overall, we found that the environmental heterogeneity of photosynthetically active radiation (PAR) and oxygen concentration ([O2]) in Lake Fryxell provide the framework by which metabolic diversity and composition of the community is structured, in accordance with its phylogenetic structure. The organization of the resulting microbial ecosystems are consistent with the maximum power principle and the species sorting model.

The genetic and cultural evolution of unsustainability

Anthropogenic changes are accelerating and threaten the future of life on earth. While the proximate mechanisms of these anthropogenic changes are well studied (e.g., climate change, biodiversity loss, population growth), the evolutionary causality of these anthropogenic changes have been largely ignored. Anthroecological theory (AET) proposes that the ultimate cause of anthropogenic environmental change is multi-level selection for niche construction and ecosystem engineering. Here, we integrate this theory with Lotka’s Maximum Power Principle and propose a model linking energy extraction from the environment with genetic, technological and cultural evolution to increase human ecosystem carrying capacity. Carrying capacity is partially determined by energetic factors such as the net energy a population can acquire from its environment and the efficiency of conversion from energy input to offspring output. These factors are under Darwinian genetic selection in all species, but in humans, they are also determined by technology and culture. If there is genetic or non-genetic heritable variation in the ability of an individual or social group to increase its carrying capacity, then we hypothesize that selection or cultural evolution will act to increase carrying capacity. Furthermore, if this evolution of carrying capacity occurs faster than the biotic components of the ecological system can respond via their own evolution, then we hypothesize that unsustainable ecological changes will result.

Ecological economics for humanity’s plague phase

The human enterprise is in potentially disastrous ‘overshoot’, exploiting the ecosphere beyond ecosystems’ regenerative capacity and filling natural waste sinks to overflowing. Economic behavior that was once ‘rational’ has become maladaptive. This situation is the inevitable outcome of humanity’s natural expansionist tendencies reinforced by ecologically vacuous growth-oriented ‘neoliberal’ economic theory. The world needs a more ecologically-informed economics yet, despite its self-description, contemporary ‘ecological economics’ does not adequately reflect key elements of human evolutionary and behavioral ecology. How should the discipline develop? This paper briefly considers some of the missing pieces that are particularly relevant to humanity’s econo-ecological predicament: competitive displacement of non-human species through habitat and resource appropriation; humans as exemplars of the maximum power principle; the implications of ‘far-from-equilibrium’ thermodynamics; and evidence that H. sapiens is in the plague phase of a global population cycle. I then describe some of motivational and cognitive roots of crisis denial that extend even into the 2015 Paris climate accord. The paper concludes with: a) a list of principles for ecological economics consistent with the analysis and; b) a minimal set of policy actions necessary for the global community to achieve a more equitable steady-state economy and stable population within the biocapacity of nature.

Can the “Maximum Power Principle” Be Applied to Pulsed Dielectric Barrier Discharge?

In this paper, we report a qualitative model of operation and energy release in pulsed dielectric barrier discharges (DBDs). We demonstrate that pulsed DBDs operate according to the “maximum power principle” and explain the relevant physical processes. Compared to experimental data, the proposed model allows an accurate estimation of the discharge pulse energy as a function of dielectric properties, electrode size, and pulse parameters (shape and voltage amplitude).

Thermodynamic Way of Ranking Heat-Transfer Mechanisms

Known mechanisms of heat transfer are ranked according to the efficiency of heat conversion at the maximum work load, according to Alikhanov’s thermodynamic principle of maximum power.

Thermodynamics of metabolic energy conversion under muscle load

The metabolic processes complexity is at the heart of energy conversion in living organisms and forms a huge obstacle to develop tractable thermodynamic metabolism models. By raising our analysis to a higher level of abstraction, we develop a compact—i.e. relying on a reduced set of parameters—thermodynamic model of metabolism, in order to analyse the chemical-to-mechanical energy conversion under muscle load, and give a thermodynamic ground to Hill’s seminal muscular operational response model. Living organisms are viewed as dynamical systems experiencing a feedback loop in the sense that they can be considered as thermodynamic systems subjected to mixed boundary conditions, coupling both potentials and fluxes. Starting from a rigorous derivation of generalized thermoelastic and transport coefficients, leading to the definition of a metabolic figure of merit, we establish the expression of the chemical-mechanical coupling, and specify the nature of the dissipative mechanism and the so-called figure of merit. The particular nature of the boundary conditions of such a system reveals the presence of a feedback resistance, representing an active parameter, which is crucial for the proper interpretation of the muscle response under effort in the framework of Hill’s model. We also develop an exergy analysis of the so-called maximum power principle, here understood as a particular configuration of an out-of-equilibrium system, with no supplemental extremal principle involved.

Multiscale analysis of autotroph-heterotroph interactions in a high-temperature microbial community

Interactions among microbial community members can lead to emergent properties, such as enhanced productivity, stability, and robustness. Iron-oxide mats in acidic (pH 2–4), high-temperature (> 65 °C) springs of Yellowstone National Park contain relatively simple microbial communities and are well-characterized geochemically. Consequently, these communities are excellent model systems for studying the metabolic activity of individual populations and key microbial interactions. The primary goals of the current study were to integrate data collected in situ with in silico calculations across process-scales encompassing enzymatic activity, cellular metabolism, community interactions, and ecosystem biogeochemistry, as well as to predict and quantify the functional limits of autotroph-heterotroph interactions. Metagenomic and transcriptomic data were used to reconstruct carbon and energy metabolisms of an important autotroph (Metallosphaera yellowstonensis) and heterotroph (Geoarchaeum sp. OSPB) from the studied Fe(III)-oxide mat communities. Standard and hybrid elementary flux mode and flux balance analyses of metabolic models predicted cellular- and community-level metabolic acclimations to simulated environmental stresses, respectively. In situ geochemical analyses, including oxygen depth-profiles, Fe(III)-oxide deposition rates, stable carbon isotopes and mat biomass concentrations, were combined with cellular models to explore autotroph-heterotroph interactions important to community structure-function. Integration of metabolic modeling with in situ measurements, including the relative population abundance of autotrophs to heterotrophs, demonstrated that Fe(III)-oxide mat communities operate at their maximum total community growth rate (i.e. sum of autotroph and heterotroph growth rates), as opposed to net community growth rate (i.e. total community growth rate subtracting autotroph consumed by heterotroph), as predicted from the maximum power principle. Integration of multiscale data with ecological theory provides a basis for predicting autotroph-heterotroph interactions and community-level cellular organization.

Robust stability of closed artificial ecosystem cultivating cabbage realized by ecological thermodynamics and dissipative structure system

The environmental disturbances often negatively influence normal operation of closed artificial ecosystems (CAE). In this paper, a specific CAE cultivating cabbage (CAECC) was considered as a dissipative structure system (DSS), its highly precise kinetic model was developed by system dynamics and experimental data. Based on ecological thermodynamics (ET) and DSS, the optimal feedback control law of light intensity, temperature and aerating rate was obtained from the stored-energy function and Odum’s maximum power principle. The digital simulation results showed that the closed-loop CAECC control system could be stabilized at a prescribed working point with desired dynamic response characteristics, accompanied with conducting eco-work and dissipation of the stored energy generated by environmental disturbances with different strengths. This research will lay a theoretical and methodological basis for construction and operation of CAE.

An Economy Viewed as a Far-from-Equilibrium System from the Perspective of Algorithmic Information Theory.

This paper, using Algorithmic Information Theory (AIT), argues that once energy resources are considered, an economy, like an ecology, requires continuous energy to be sustained in a homeostatic state away from the decayed state of its (local) thermodynamic equilibrium. AIT identifies how economic actions and natural laws create an ordered economy through what is seen as computations on a real world Universal Turing Machine (UTM) that can be simulated to within a constant on a laboratory UTM. The shortest, appropriately coded, programme to do this defines the system’s information or algorithmic entropy. The computational behaviour of many generations of primitive economic agents can create a more ordered and advanced economy, able to be specified by a relatively short algorithm. The approach allows information flows to be tracked in real-world computational processes where instructions carried in stored energy create order while ejecting disorder. Selection processes implement the Maximum Power Principle while the economy trends towards Maximum Entropy Production, as tools amplify human labour and interconnections create energy efficiency. The approach provides insights into how an advanced economy is a more ordered economy, and tools to investigate the concerns of the Bioeconomists over long term economic survival.

Measuring ecological characteristics of environmental building performance: Suggestion of an information-network model and indices to quantify complexity, power, and sustainability of energetic organization

The authors present preliminary study in pursuance of developing a flow network-based methodology of building performance evaluation, as current efficiency-centered methods do not fully account for the complex building performance in which nature, economy, and humans are inseparably involved. Based on the principle of entropy, this study defines building as a thermodynamic system that networks useful resources―energy, material and information―through close interconnection with the global environment. Measures of information content in energy-flow networking and ecological performance indicators from Shannon’s information theory, Ulanowicz’s ascendency principle, and Odum’s maximum empower principle are discussed and integratively applied to developing a generic building performance evaluation model. For the holistic indication of building sustainability, this work attempts to reconcile Ulanowicz’s and Odum’s statements about ecosystem development and also integrates emergy (spelled with an “m”) and information metrics. Environmental behaviour of the building model was tested with simulation to validate consistency with system-level principles. Results reveal that network complexity corresponds to system power and resilience (L) and fitness (F) tend to peak at an intermediate level of efficiency. This finding demonstrates applicability of Odum’s maximum power principle to building study, suggesting that increasing complexity (and power) of emergy-flow networking be a fundamental characteristic of sustainable building performance.

A Thermodynamic Analysis of Soil Ecosystem Development in Northern Wetlands

The Maximum Power Principle (MPP) — a theoretical construct that argues that systems develop to maximize energy throughput, or power — is the subject of few empirical studies. We used the MPP to explore the thermodynamic basis for microbial processes and greenhouse gas fluxes in high latitude peat soils. Increasing temperatures cause extensive areas of permafrost degradation, which can lead to wetland formation, though permafrost degradation and aggradation can be cyclical under the right conditions. Differential ecosystem responses to permafrost degradation offer an opportunity to use the unifying approach of thermodynamics. We used adenosine triphosphate (ATP) production in peat soils as a soil-relevant proxy for power to test the MPP along a chronosequence of wetlands with time following permafrost degradation. We conducted soil incubation experiments and measured production rates of CO2, methane (CH4), nitrous oxide (N2O), and ATP. ATP production was significantly lower (p < 0.05) in the young bog soils compared to the undisturbed permafrost bog soils; rates in the older bog soils were not different from either site. Our results suggest that power output increased following recovery from permafrost thaw. A unifying vantage point provided by thermodynamics may be useful in other investigations of wetland ecosystems with unpredictable responses to disturbance.

The Farm as a Thermodynamic System: Implications of the Maximum Power Principle

A farm can be considered a thermodynamic system that uses exosomatic energy (fertilizers and pesticides) to facilitate crop yield derived from endosomatic (photosynthetically derived) energy. Because farms are thermodynamic systems, they are subject to the Maximum Power Principle. This means that farmers can maximize yield to increase economic competitiveness or maximize exosomatic energy use efficiency to minimize pollution, but they cannot do both at the same time. To maintain competitiveness, farmers usually choose to maximize yield, a decision that often results in degradation of the environmental commons. Farms are self-organizing systems in that yield is converted to dollars, some of which the farmer uses to manage cropping systems embedded in the farming system. If management of an industrial cropping system is modified to use nature’s services, energy use efficiency of the farm increases and pollution is reduced.

A symbol timing recovery algorithm of M-PSK signals for burst modem applications with small packet size

Feedforward symbol timing recovery techniques are particularly important for initial acquisition in burst modems. However, these techniques either have large calculation burden or sensitive to frequency offsets. In this paper, we proposed an efficient symbol timing recovery algorithm of MPSK signals named OMQ (Ordered Maximum power using Quadratic approximation partially) algorithm which is based on the Quadratic Approximation (QA) algorithm. We used ordered statistic sorting method to reduce the computational complexity further, meanwhile maximum mean power principle was used to decrease frequency offset sensitivity. The proposed algorithm adopts estimation-down sampling structure which is suitable for small packet size transmission. The results show that, while comparing with the QA algorithm, the computational complexity is reduced by 75% at most when 8 samples per symbol are used. The proposed algorithm shows better performance in terms of the jitter variance and sensitivity to frequency offsets.